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<div class="title">TensorContractionSycl.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">// This file is part of Eigen, a lightweight C++ template library for linear algebra.</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// Mehdi Goli    Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">// Ralph Potter  Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment">// Luke Iwanski  Codeplay Software Ltd.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment">// Contact: &lt;eigen@codeplay.com&gt;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment">// This Source Code Form is subject to the terms of the Mozilla Public License v. 2.0. If a copy of the MPL was not</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment">/*****************************************************************</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * TensorContractionSycl.h</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * \brief:</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *  TensorContractionSycl.h, provides various tensor contraction kernel for SYCL backend</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> *****************************************************************/</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160; </div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="preprocessor">#ifndef EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_SYCL_H</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#define EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_SYCL_H</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160; </div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="preprocessor">#include &quot;./InternalHeaderCheck.h&quot;</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespaceEigen.html">Eigen</a> {</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160; </div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="keyword">namespace </span>TensorSycl {</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="keyword">namespace </span>internal {</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_GEMV</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keyword">typename</span> StorageIndex, StorageIndex NCWindow, StorageIndex CFactor, StorageIndex NCFactor&gt;</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="keyword">struct </span>TVPanelSize {</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  <span class="comment">// LocalThreadSizeC: determines total number of thread per workgroup for the contracting dimension</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LocalThreadSizeC = EIGEN_SYCL_LOCAL_THREAD_DIM0;</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  <span class="comment">// LocalThreadSizeNC: determines total number of thread per workgroup for the non-contracting dimension</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LocalThreadSizeNC = EIGEN_SYCL_LOCAL_THREAD_DIM1;</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  <span class="comment">// TileSizeDimNC: determines the tile size for the non-contracting dimension</span></div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex TileSizeDimNC = NCWindow / NCFactor;</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  <span class="comment">// TileSizeDimC: determines the tile size for the contracting dimension</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex TileSizeDimC = CFactor * LocalThreadSizeNC * LocalThreadSizeC;</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;  <span class="comment">// WorkLoadPerThreadNC : determines workload per thread for loading the non-contracting dimension</span></div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadNC = TileSizeDimNC / LocalThreadSizeNC;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  <span class="comment">// WorkLoadPerThreadC: determines workload per thread for loading the non-contracting dimension</span></div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadC = TileSizeDimC / LocalThreadSizeC;</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="comment">// BC : determines if supporting bank conflict is required</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> BC = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;};</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Scalar, <span class="keyword">typename</span> StorageIndex, StorageIndex REG_SIZE_M, StorageIndex REG_SIZE_N, StorageIndex TSDK&gt;</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="keyword">struct </span>TTPanelSize {</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  <span class="comment">// TileSizeDimK: determines Tile size for dimension K. The packet size is assumed to be considered</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex TileSizeDimK = TSDK;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  <span class="comment">// WorkLoadPerThreadM : determines workload per thread for loading the M dimension This can be varied based on the</span></div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  <span class="comment">// available register on a chosen device(can be controlled by EIGEN_SYCL_REG_M macro//</span></div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_REG_M</span></div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadM = REG_SIZE_M;</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadM = EIGEN_SYCL_REG_M;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;<span class="comment">// WorkLoadPerThreadN : determines workload per thread for loading the N dimension This can be varied based on the</span></div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;<span class="comment">// available register on a chosen device(can be controlled by EIGEN_SYCL_REG_N macro</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_REG_N</span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadN = REG_SIZE_N;</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadN = EIGEN_SYCL_REG_N;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;  <span class="comment">// LocalThreadSizeM: determines total number of thread per workgroup for the m dimension</span></div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LocalThreadSizeM = EIGEN_SYCL_LOCAL_THREAD_DIM0;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  <span class="comment">// LocalThreadSizeN: determines total number of thread per workgroup for the n dimension</span></div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LocalThreadSizeN = EIGEN_SYCL_LOCAL_THREAD_DIM1;</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;  <span class="comment">// TileSizeDimM: determines the tile size for the m dimension</span></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex TileSizeDimM = LocalThreadSizeM * WorkLoadPerThreadM;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="comment">// TileSizeDimN: determines the tile size for the n dimension</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex TileSizeDimN = LocalThreadSizeN * WorkLoadPerThreadN;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  <span class="comment">// LoadPerThreadLhs: determines workload per thread for loading Lhs Tensor. This must be divisable by packetsize</span></div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LoadPerThreadLhs =</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      ((TileSizeDimK * WorkLoadPerThreadM * WorkLoadPerThreadN) / (TileSizeDimN));</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  <span class="comment">// LoadPerThreadRhs: determines workload per thread for loading Rhs Tensor. This must be divisable by packetsize</span></div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LoadPerThreadRhs =</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      ((TileSizeDimK * WorkLoadPerThreadM * WorkLoadPerThreadN) / (TileSizeDimM));</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  <span class="comment">// BC : determines if supporting bank conflict is required</span></div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> BC = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  <span class="comment">// DoubleBuffer: determines if double buffering technique should be used (This can be disabled by</span></div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;  <span class="comment">// EIGEN_SYCL_DISABLE_DOUBLE_BUFFER macro when the device does not have sufficient local memory)</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> DoubleBuffer =</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_DISABLE_DOUBLE_BUFFER</span></div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      <span class="keyword">false</span>;</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;      <span class="keyword">true</span>;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;};</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160; </div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;<span class="comment">/* !</span></div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;<span class="comment"> * \brief contraction_type: an enum class representing the Tensor Contraction implementation algorithm. This is used to</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;<span class="comment"> * specialize the contraction algorithm based on device support for dedicated local memory.</span></div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;<span class="keyword">enum class</span> contraction_type { local, no_local };</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;<span class="comment">/* !</span></div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;<span class="comment"> * \brief data_source an enum class determining the location of the data in a memory hierarchy (global, local, private).</span></div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;<span class="keyword">enum class</span> data_source { global_mem, local_mem, private_mem };</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> PacketLoad, <span class="keywordtype">bool</span> is_coalesced_layout, bool, <span class="keyword">typename</span> PacketType, <span class="keyword">typename</span> TensorMapper,</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;          <span class="keyword">typename</span> StorageIndex&gt;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;<span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::enable_if_t&lt;PacketLoad, PacketType&gt; read(</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keyword">const</span> TensorMapper &amp;tensorMapper, <span class="keyword">const</span> StorageIndex &amp;NCIndex, <span class="keyword">const</span> StorageIndex &amp;CIndex, <span class="keyword">const</span> StorageIndex &amp;ld) {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  <span class="keyword">const</span> StorageIndex row = (is_coalesced_layout) ? NCIndex : CIndex;</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  <span class="keyword">const</span> StorageIndex col = (is_coalesced_layout) ? CIndex : NCIndex;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  <span class="keywordflow">return</span> tensorMapper.get_tensor().template packet&lt;Unaligned&gt;(row + (col * ld));</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;}</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160; </div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> PacketLoad, <span class="keywordtype">bool</span>, <span class="keywordtype">bool</span> IsRhs, <span class="keyword">typename</span> PacketType, <span class="keyword">typename</span> TensorMapper, <span class="keyword">typename</span> StorageIndex&gt;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;<span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::enable_if_t&lt;!PacketLoad, PacketType&gt; read(</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    <span class="keyword">const</span> TensorMapper &amp;tensorMapper, <span class="keyword">const</span> StorageIndex &amp;NCIndex, <span class="keyword">const</span> StorageIndex &amp;CIndex, <span class="keyword">const</span> StorageIndex &amp;) {</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="keyword">const</span> StorageIndex row = (IsRhs) ? CIndex : NCIndex;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  <span class="keyword">const</span> StorageIndex col = (IsRhs) ? NCIndex : CIndex;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  <span class="keywordflow">return</span> tensorMapper(row, col);</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;}</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160; </div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> StorageIndex, StorageIndex ld, data_source dt, <span class="keyword">typename</span> PacketType, <span class="keyword">typename</span> DataScalar&gt;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;<span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    std::enable_if_t&lt;dt != data_source::global_mem, void&gt;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    write(PacketType &amp;packet_data, DataScalar ptr) {</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  EIGEN_CONSTEXPR <span class="keywordtype">int</span> PacketSize = Eigen::internal::unpacket_traits&lt;PacketType&gt;::size;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; PacketSize; i++) {</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    *ptr = PacketWrapper&lt;PacketType, PacketSize&gt;::scalarize(i, packet_data);</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    ptr += ld;</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  }</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;}</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160; </div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;<span class="keyword">template</span> &lt;data_source dt, <span class="keyword">typename</span> PacketType, <span class="keyword">typename</span> DataScalar&gt;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;<span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> std::enable_if_t&lt;</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    Eigen::internal::unpacket_traits&lt;PacketType&gt;::size != 1 &amp;&amp; dt == data_source::global_mem, <span class="keywordtype">void</span>&gt;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;write(PacketType &amp;packet_data, DataScalar *ptr) {</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;  ::Eigen::internal::pstoreu&lt;DataScalar, PacketType&gt;(ptr, packet_data);</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;}</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160; </div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;<span class="keyword">template</span> &lt;data_source dt, <span class="keyword">typename</span> PacketType, <span class="keyword">typename</span> DataScalar&gt;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;<span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keyword">typename</span> std::enable_if_t&lt;</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    Eigen::internal::unpacket_traits&lt;PacketType&gt;::size == 1 &amp;&amp; dt == data_source::global_mem, <span class="keywordtype">void</span>&gt;</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;write(PacketType &amp;packet_data, DataScalar *ptr) {</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;  *ptr = packet_data;</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;}</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160; </div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_<span class="keywordtype">int</span>ernal&gt;</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">bool</span> check_boundary(<span class="keywordtype">bool</span>) {</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;}</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160; </div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;<span class="keyword">template</span> &lt;&gt;</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">bool</span> check_boundary&lt;false&gt;(<span class="keywordtype">bool</span> cond) {</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;  <span class="keywordflow">return</span> cond;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;}</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_transposed, <span class="keywordtype">bool</span> is_rhs_, <span class="keywordtype">bool</span> packet_load_, <span class="keyword">typename</span> PacketType&gt;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;<span class="keyword">struct </span>BlockProperties {</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> packet_load = packet_load_;</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::internal::unpacket_traits&lt;PacketType&gt;::type OutScalar;</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_rhs = is_rhs_;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;  <span class="keyword">typedef</span> std::conditional_t&lt;packet_load, PacketType, OutScalar&gt; OutType;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> elements_per_access = Eigen::internal::unpacket_traits&lt;OutType&gt;::size;</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_coalesced_layout = !(is_transposed ^ is_rhs);</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> nc_stride = (is_coalesced_layout ? elements_per_access : 1);</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> c_stride = (is_coalesced_layout ? 1 : elements_per_access);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;};</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160; </div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> StorageIndex&gt;</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;<span class="keyword">struct </span>ThreadProperties {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;  <span class="keyword">const</span> StorageIndex linearLocalThreadId;</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;  <span class="keyword">const</span> StorageIndex kGroupId;</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;  <span class="keyword">const</span> StorageIndex mGroupOffset;</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;  <span class="keyword">const</span> StorageIndex nGroupOffset;</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;  <span class="keyword">const</span> StorageIndex kGroupOffset;</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;  <span class="keyword">const</span> StorageIndex mLocalOffset;</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;  <span class="keyword">const</span> StorageIndex nLocalOffset;</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;  <span class="keyword">const</span> StorageIndex mGlobalOffset;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;  <span class="keyword">const</span> StorageIndex nGlobalOffset;</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;  StorageIndex kSize;</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_internal;</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;  <span class="comment">// this is used to adjust the last block</span></div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ThreadProperties(</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;      <span class="keyword">const</span> StorageIndex linearLocalThreadId_, <span class="keyword">const</span> StorageIndex kGroupId_, <span class="keyword">const</span> StorageIndex mGroupOffset_,</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;      <span class="keyword">const</span> StorageIndex nGroupOffset_, <span class="keyword">const</span> StorageIndex kGroupOffset_, <span class="keyword">const</span> StorageIndex mLocalOffset_,</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;      <span class="keyword">const</span> StorageIndex nLocalOffset_, <span class="keyword">const</span> StorageIndex mGlobalOffset_, <span class="keyword">const</span> StorageIndex nGlobalOffset_,</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;      StorageIndex kSize_, <span class="keyword">const</span> <span class="keywordtype">bool</span> is_internal_)</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;      : linearLocalThreadId(linearLocalThreadId_),</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;        kGroupId(kGroupId_),</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;        mGroupOffset(mGroupOffset_),</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;        nGroupOffset(nGroupOffset_),</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;        kGroupOffset(kGroupOffset_),</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;        mLocalOffset(mLocalOffset_),</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;        nLocalOffset(nLocalOffset_),</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;        mGlobalOffset(mGlobalOffset_),</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;        nGlobalOffset(nGlobalOffset_),</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;        kSize(kSize_),</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;        is_internal(is_internal_) {}</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;};</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160; </div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OutScalar, <span class="keyword">typename</span> LhsScalar, <span class="keyword">typename</span> RhsScalar, <span class="keyword">typename</span> OutAccessor, <span class="keyword">typename</span> LhsMapper,</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;          <span class="keyword">typename</span> RhsMapper, <span class="keyword">typename</span> StorageIndex, <span class="keyword">typename</span> Properties, <span class="keyword">typename</span> TripleDim, <span class="keywordtype">bool</span> Vectorizable,</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;          <span class="keyword">typename</span> input_mapper_properties, <span class="keywordtype">bool</span> IsFinal, contraction_type contraction_tp&gt;</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;<span class="keyword">class </span>TensorContractionKernel {</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160; <span class="keyword">public</span>:</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::TensorSycl::internal::Vectorise&lt;OutScalar, Eigen::SyclDevice, Vectorizable&gt;::PacketReturnType</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;      PacketReturnType;</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> PacketSize =</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;      Eigen::TensorSycl::internal::Vectorise&lt;OutScalar, Eigen::SyclDevice, Vectorizable&gt;::PacketSize;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_lhs_transposed =</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;      !::Eigen::internal::TensorContractionInputMapperTrait&lt;LhsMapper&gt;::inner_dim_contiguous;</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_rhs_transposed =</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;      !::Eigen::internal::TensorContractionInputMapperTrait&lt;RhsMapper&gt;::inner_dim_contiguous;</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160; </div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;  <span class="keyword">typedef</span> BlockProperties&lt;is_lhs_transposed, <span class="keyword">false</span>, input_mapper_properties::is_lhs_matrix &amp;&amp; Vectorizable,</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;                          PacketReturnType&gt;</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;      LHSBlockProperties;</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160; </div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;  <span class="keyword">typedef</span> BlockProperties&lt;is_rhs_transposed, <span class="keyword">true</span>, input_mapper_properties::is_rhs_matrix &amp;&amp; Vectorizable,</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;                          PacketReturnType&gt;</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;      RHSBlockProperties;</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160; </div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex NStride =</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;      contraction_tp == contraction_type::local ? Properties::WorkLoadPerThreadN : RHSBlockProperties::nc_stride;</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160; </div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;OutScalar, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt; Scratch;</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;  <span class="keyword">typedef</span> cl::sycl::multi_ptr&lt;OutScalar, cl::sycl::access::address_space::local_space&gt; local_ptr;</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;  <span class="keyword">typedef</span> OutScalar * <span class="comment">/*cl::sycl::multi_ptr&lt;OutScalar, cl::sycl::access::address_space::private_space&gt;*/</span> private_ptr;</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  <span class="keyword">typedef</span> std::conditional_t&lt;contraction_tp == contraction_type::local, local_ptr, private_ptr&gt;</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;          tile_ptr;</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LSDL = contraction_tp == contraction_type::local</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;                                                 ? Properties::TileSizeDimM + Properties::BC</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;                                                 : Properties::WorkLoadPerThreadM;</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LSDR = contraction_tp == contraction_type::local</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;                                                 ? Properties::TileSizeDimN + Properties::BC</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;                                                 : Properties::WorkLoadPerThreadN;</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex LocalOffset = Properties::LocalThreadSizeM * Properties::LocalThreadSizeN;</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160; </div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;  <span class="keyword">template</span> &lt;contraction_type, StorageIndex&gt;</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;  <span class="keyword">struct </span>MemHolder {</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    tile_ptr ptr;</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE MemHolder(local_ptr block_start_ptr) : ptr(block_start_ptr) {}</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;  };</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;  <span class="keyword">template</span> &lt;StorageIndex MemSize&gt;</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;  <span class="keyword">struct </span>MemHolder&lt;contraction_type::no_local, MemSize&gt; {</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    OutScalar ptr[MemSize] = {OutScalar{0}};</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;  };</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;  <span class="keyword">struct </span>TiledMemory {</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;    MemHolder&lt;contraction_tp, Properties::WorkLoadPerThreadM * Properties::TileSizeDimK&gt; lhs_scratch_extract;</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;    MemHolder&lt;contraction_tp, Properties::WorkLoadPerThreadN * Properties::TileSizeDimK&gt; rhs_scratch_extract;</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    tile_ptr lhs_scratch_ptr_compute;</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;    tile_ptr rhs_scratch_ptr_compute;</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;    <span class="keyword">const</span> std::pair&lt;StorageIndex, StorageIndex&gt; lhs_extract_index;</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;    <span class="keyword">const</span> std::pair&lt;StorageIndex, StorageIndex&gt; rhs_extract_index;</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;    <span class="keyword">template</span> &lt;contraction_type tp = contraction_tp&gt;</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;    TiledMemory(<span class="keyword">const</span> ThreadProperties&lt;StorageIndex&gt; &amp;, local_ptr,</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;                std::enable_if_t&lt;tp == contraction_type::no_local&gt; * = 0)</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;        : lhs_scratch_extract{},</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;          rhs_scratch_extract{},</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;          lhs_scratch_ptr_compute(lhs_scratch_extract.ptr),</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;          rhs_scratch_ptr_compute(rhs_scratch_extract.ptr),</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;          lhs_extract_index(std::pair&lt;StorageIndex, StorageIndex&gt;(StorageIndex{0}, StorageIndex{0})),</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;          rhs_extract_index(std::pair&lt;StorageIndex, StorageIndex&gt;(StorageIndex{0}, StorageIndex{0})) {}</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160; </div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;    <span class="keyword">template</span> &lt;contraction_type tp = contraction_tp&gt;</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;    TiledMemory(<span class="keyword">const</span> ThreadProperties&lt;StorageIndex&gt; &amp;thread_properties, local_ptr block_start_ptr,</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;                std::enable_if_t&lt;tp == contraction_type::local&gt; * = 0)</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;        : lhs_scratch_extract{block_start_ptr},</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;          rhs_scratch_extract{lhs_scratch_extract.ptr +</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;                              ((Properties::DoubleBuffer + 1) * LSDL * Properties::TileSizeDimK)},</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;          lhs_scratch_ptr_compute(lhs_scratch_extract.ptr + thread_properties.mLocalOffset),</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;          rhs_scratch_ptr_compute(rhs_scratch_extract.ptr + thread_properties.nLocalOffset),</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;          lhs_extract_index(</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;              local_id_extract&lt;LHSBlockProperties, Properties::TileSizeDimM&gt;(thread_properties.linearLocalThreadId)),</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;          rhs_extract_index(</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;              local_id_extract&lt;RHSBlockProperties, Properties::TileSizeDimN&gt;(thread_properties.linearLocalThreadId)) {}</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;  };</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160; </div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;  Scratch scratch;</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;  <span class="keyword">const</span> LhsMapper lhs;</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;  <span class="keyword">const</span> RhsMapper rhs;</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;  OutAccessor out_res;</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;  <span class="keyword">const</span> StorageIndex groupSizeM;</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;  <span class="keyword">const</span> StorageIndex groupSizeN;</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;  <span class="keyword">const</span> StorageIndex numTiles;</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;  <span class="keyword">const</span> TripleDim triple_dim;</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160; </div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorContractionKernel(Scratch scratch_, <span class="keyword">const</span> LhsMapper lhs_,</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;                                                                <span class="keyword">const</span> RhsMapper rhs_, OutAccessor out_res_,</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;                                                                <span class="keyword">const</span> StorageIndex groupSizeM_,</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;                                                                <span class="keyword">const</span> StorageIndex groupSizeN_,</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;                                                                <span class="keyword">const</span> StorageIndex numTiles_,</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;                                                                <span class="keyword">const</span> TripleDim triple_dim_)</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;      : scratch(scratch_),</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;        lhs(lhs_),</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;        rhs(rhs_),</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;        out_res(out_res_),</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;        groupSizeM(groupSizeM_),</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;        groupSizeN(groupSizeN_),</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;        numTiles(numTiles_),</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;        triple_dim(triple_dim_) {}</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160; </div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorContractionKernel(Scratch scratch_, <span class="keyword">const</span> LhsMapper lhs_,</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;                                                                <span class="keyword">const</span> RhsMapper rhs_, OutAccessor out_res_,</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;                                                                <span class="keyword">const</span> StorageIndex groupSizeM_,</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;                                                                <span class="keyword">const</span> StorageIndex numTiles_,</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;                                                                <span class="keyword">const</span> TripleDim triple_dim_)</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;      : TensorContractionKernel(scratch_, lhs_, rhs_, out_res_, groupSizeM_, 1, numTiles_, triple_dim_) {}</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160; </div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;    <span class="keyword">const</span> StorageIndex linearLocalThreadId = itemID.get_local_id(0);</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;    <span class="keyword">const</span> StorageIndex nLocalThreadId = linearLocalThreadId / Properties::LocalThreadSizeM;</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;    <span class="keyword">const</span> StorageIndex mLocalThreadId = linearLocalThreadId % Properties::LocalThreadSizeM;</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;    <span class="keyword">const</span> StorageIndex mGroupId = itemID.get_group(0) % groupSizeM;</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;    <span class="keyword">const</span> StorageIndex tmp = itemID.get_group(0) / groupSizeM;</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;    <span class="keyword">const</span> StorageIndex nGroupId = IsFinal ? tmp : tmp % groupSizeN;</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;    <span class="keyword">const</span> StorageIndex kGroupId = IsFinal ? 0 : tmp / groupSizeN;</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;    <span class="keyword">const</span> StorageIndex mGroupOffset = mGroupId * Properties::TileSizeDimM;</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;    <span class="keyword">const</span> StorageIndex nGroupOffset = nGroupId * Properties::TileSizeDimN;</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;    <span class="keyword">const</span> StorageIndex mLocalOffset = PacketSize * mLocalThreadId;</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;    <span class="keyword">const</span> StorageIndex nLocalOffset = NStride * nLocalThreadId;</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;    <span class="keyword">const</span> StorageIndex mGlobalOffset = mGroupOffset + mLocalOffset;</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;    <span class="keyword">const</span> StorageIndex nGlobalOffset = nGroupOffset + nLocalOffset;</div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160; </div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;    <span class="keyword">const</span> StorageIndex kSizePerWG = IsFinal ? triple_dim.K : numTiles * Properties::TileSizeDimK;</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;    StorageIndex kGroupOffset = kGroupId * kSizePerWG;</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_internal = triple_dim.M - mGroupOffset &gt;= Properties::TileSizeDimM &amp;&amp;</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;                             triple_dim.N - nGroupOffset &gt;= Properties::TileSizeDimN &amp;&amp;</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;                             triple_dim.K - kGroupOffset &gt;= kSizePerWG;</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;    <span class="comment">// this is used to adjust the last block</span></div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;    StorageIndex kSize = IsFinal ? triple_dim.K : std::min(kSizePerWG, triple_dim.K - kGroupOffset);</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;    <span class="comment">// This is used to find out the lats K offset so that kGroupOffset -kSize can compute the coffset for loading to</span></div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;    <span class="comment">// tile</span></div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;    kGroupOffset += kSize;</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160; </div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;    <span class="keyword">auto</span> thread_properties =</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;        ThreadProperties&lt;StorageIndex&gt;(linearLocalThreadId, kGroupId, mGroupOffset, nGroupOffset, kGroupOffset,</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;                                       mLocalOffset, nLocalOffset, mGlobalOffset, nGlobalOffset, kSize, is_internal);</div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160; </div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;    <span class="keyword">auto</span> out_ptr = out_res.get_pointer() + (IsFinal ? 0 : thread_properties.kGroupId * triple_dim.M * triple_dim.N);</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160; </div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;    (thread_properties.is_internal) ? compute_panel&lt;true&gt;(itemID, thread_properties, out_ptr)</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;                                    : compute_panel&lt;false&gt;(itemID, thread_properties, out_ptr);</div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;  }</div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;  <span class="comment">// The compute block computes the contraction operation private block for each thread and store the resutl in the</span></div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;  <span class="comment">// privateRes memory of Each computation the compute block function is independent of local and no local concepts as</span></div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;  <span class="comment">// it only compute the block on each thread&#39;s private memory space</span></div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> compute_block_per_tile(OutScalar *lhs_block_ptr, OutScalar *rhs_block_ptr,</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;                                                                    PacketReturnType *privateRes) {</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;    StorageIndex idx = 0;</div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;    EIGEN_CONSTEXPR StorageIndex lhs_stride =</div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;        contraction_tp == contraction_type::local ? (PacketSize * Properties::LocalThreadSizeM) : 1;</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;    <span class="keywordflow">for</span> (StorageIndex wLPTN = 0; wLPTN &lt; Properties::WorkLoadPerThreadN; wLPTN++) {</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;      <span class="keyword">auto</span> rhsPacket = PacketReturnType{*(rhs_block_ptr + wLPTN)};</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;      StorageIndex lhs_index = 0;</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;      <span class="keywordflow">for</span> (StorageIndex wLPTM = 0; wLPTM &lt; Properties::WorkLoadPerThreadM / PacketSize; wLPTM++) {</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;        PacketReturnType lhsPack{};</div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;        Eigen::TensorSycl::internal::PacketWrapper&lt;PacketReturnType, PacketSize&gt;::set_packet(lhsPack,</div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;                                                                                             lhs_block_ptr + lhs_index);</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;        privateRes[idx] = ::Eigen::internal::pmadd(lhsPack, rhsPacket, privateRes[idx]);</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160; </div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;        lhs_index += lhs_stride;</div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;        idx++;</div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;      }</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;    }</div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;  }</div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;  <span class="comment">// The store function write the computed contraction operation in the private memory of each thread to the global</span></div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;  <span class="comment">// memory. The store function is independent of local and no local concepts s that it can be abstract out in the base</span></div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;  <span class="comment">// class.</span></div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_<span class="keywordtype">int</span>ernal_block, StorageIndex PrivateNStr<span class="keywordtype">id</span>e, <span class="keyword">typename</span> OutPtr&gt;</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> store(OutPtr *out_ptr, PacketReturnType *privateRes,</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;                                                   StorageIndex mGlobalOffset, StorageIndex nGlobalOffset) {</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;    <span class="keyword">auto</span> chk_bound = [&amp;](<span class="keyword">const</span> StorageIndex &amp;mIndex, <span class="keyword">const</span> StorageIndex &amp;nIndex) EIGEN_DEVICE_FUNC {</div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;      <span class="keywordflow">return</span> (mIndex + PacketSize - 1 &lt; triple_dim.M &amp;&amp; nGlobalOffset + nIndex &lt; triple_dim.N);</div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;    };</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;    <span class="comment">// when local memory is not used M and N are both accessed in a coalesced way. However, when local memory is</span></div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;    <span class="comment">// available the k*N is transposed in the local to N*K therefore, each blocks operates on blockId*</span></div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;    <span class="comment">// WorkLoadPerThreadN slice of N</span></div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;    EIGEN_CONSTEXPR StorageIndex GlobalNStride =</div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;        contraction_tp == contraction_type::local ? 1 : Properties::LocalThreadSizeN;</div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;    <span class="keywordflow">for</span> (StorageIndex wLPTN = 0; wLPTN &lt; Properties::WorkLoadPerThreadN / PrivateNStride; wLPTN++) {</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;      <span class="comment">// output leading dimension</span></div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;      StorageIndex outputLD = 0;</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;      <span class="comment">// When local memory is used the PrivateNstride is always 1 because the coalesed access on N is loaded into Local</span></div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;      <span class="comment">// memory and extracting from local to global is the same as no transposed version. However, when local memory is</span></div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;      <span class="comment">// not used and RHS is transposed we packetize the load for RHS.</span></div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;      <span class="keywordflow">for</span> (StorageIndex nId = 0; nId &lt; PrivateNStride; nId++) {</div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;        StorageIndex globalRow = mGlobalOffset;</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;        EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;        <span class="keywordflow">for</span> (StorageIndex wLPTM = 0; wLPTM &lt; Properties::WorkLoadPerThreadM / PacketSize; wLPTM++) {</div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;          PacketReturnType privetOut = privateRes[wLPTM];</div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;          <span class="keywordflow">if</span> (check_boundary&lt;is_internal_block&gt;(chk_bound(globalRow, nId))) {</div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;            <span class="comment">// Store the final results in C. The C matrix has always M as a first StorageIndex and N as a second</span></div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;            <span class="comment">// StorageIndex Therefore it is always coalesced layout</span></div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;            write&lt;data_source::global_mem&gt;(privetOut, out_ptr + outputLD + globalRow);</div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;          } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;            EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;            <span class="keywordflow">for</span> (StorageIndex mId = 0; mId &lt; PacketSize; mId++) {</div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;              StorageIndex mOffset = globalRow + mId;</div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;              <span class="keywordflow">if</span> (mOffset &lt; triple_dim.M &amp;&amp; (nGlobalOffset + nId &lt; triple_dim.N)) {</div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;                out_ptr[mOffset + outputLD] =</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;                    Eigen::TensorSycl::internal::PacketWrapper&lt;PacketReturnType, PacketSize&gt;::scalarize(mId, privetOut);</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160;              }</div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;            }</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;          }</div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160;          globalRow += (PacketSize * Properties::LocalThreadSizeM);</div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;        }</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;        outputLD += triple_dim.M;</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;        privateRes += Properties::WorkLoadPerThreadM / PacketSize;</div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;      }</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;      out_ptr += (GlobalNStride * outputLD);</div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160; </div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;      nGlobalOffset += (PrivateNStride * GlobalNStride);</div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;    }</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;  }</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;  <span class="comment">// when no local memory is used the following extract_block will be enabled</span></div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> InputBlockProperties, <span class="keywordtype">bool</span> is_internal_block, <span class="keyword">typename</span> Input, <span class="keyword">typename</span> PrivateReg,</div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;            contraction_type contract_tp = contraction_tp&gt;</div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;      std::enable_if_t&lt;contract_tp == contraction_type::no_local&gt;</div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;      extract_block(<span class="keyword">const</span> Input &amp;inpt, PrivateReg private_ptr, <span class="keyword">const</span> std::pair&lt;StorageIndex, StorageIndex&gt; &amp;,</div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;                    <span class="keyword">const</span> StorageIndex &amp;ncOffset, <span class="keyword">const</span> StorageIndex cOffset) {</div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;    EIGEN_CONSTEXPR StorageIndex LocalThreadSizeNC =</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;        InputBlockProperties::is_rhs ? Properties::LocalThreadSizeN : Properties::LocalThreadSizeM;</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;    EIGEN_CONSTEXPR StorageIndex WorkLoadPerThreadNC =</div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;        InputBlockProperties::is_rhs ? Properties::WorkLoadPerThreadN : Properties::WorkLoadPerThreadM;</div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;    <span class="keyword">const</span> StorageIndex &amp;NC = InputBlockProperties::is_rhs ? triple_dim.N : triple_dim.M;</div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160; </div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;    <span class="keyword">auto</span> chk_bound = [&amp;](<span class="keyword">const</span> StorageIndex &amp;CIndex, <span class="keyword">const</span> StorageIndex &amp;NCIndex) EIGEN_DEVICE_FUNC {</div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;      <span class="keywordflow">return</span> ((CIndex + InputBlockProperties::c_stride - 1 &lt; triple_dim.K) &amp;&amp;</div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;              (NCIndex + InputBlockProperties::nc_stride - 1 &lt; NC));</div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;    };</div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;    <span class="keyword">const</span> StorageIndex ld = InputBlockProperties::is_coalesced_layout ? NC : triple_dim.K;</div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;    StorageIndex cIndex = cOffset;</div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160; </div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;    <span class="keywordflow">for</span> (StorageIndex cId = 0; cId &lt; Properties::TileSizeDimK / InputBlockProperties::c_stride; cId++) {</div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;      StorageIndex ncIndex = ncOffset;</div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;      <span class="keywordflow">for</span> (StorageIndex ncId = 0; ncId &lt; WorkLoadPerThreadNC / InputBlockProperties::nc_stride; ncId++) {</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;        <span class="keywordflow">if</span> (check_boundary&lt;is_internal_block&gt;(chk_bound(cIndex, ncIndex))) {</div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;          <span class="keyword">auto</span> val =</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160;              read&lt;InputBlockProperties::packet_load, InputBlockProperties::is_coalesced_layout,</div>
<div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160;                   InputBlockProperties::is_rhs, <span class="keyword">typename</span> InputBlockProperties::OutType&gt;(inpt, ncIndex, cIndex, ld);</div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160; </div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;          write&lt;StorageIndex, (InputBlockProperties::is_coalesced_layout ? 1 : WorkLoadPerThreadNC),</div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;                data_source::private_mem&gt;(val, private_ptr);</div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;          EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;          <span class="keywordflow">for</span> (StorageIndex i = 0; i &lt; InputBlockProperties::elements_per_access; i++) {</div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;            <span class="keyword">const</span> StorageIndex ncInd = ncIndex + (InputBlockProperties::is_coalesced_layout ? i : 0);</div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;            <span class="keyword">const</span> StorageIndex cInd = cIndex + (InputBlockProperties::is_coalesced_layout ? 0 : i);</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;            OutScalar val =</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;                (ncInd &lt; NC &amp;&amp; cInd &lt; triple_dim.K)</div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;                    ? read&lt;false, InputBlockProperties::is_coalesced_layout, InputBlockProperties::is_rhs, OutScalar&gt;(</div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;                          inpt, ncInd, cInd, ld)</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;                    : OutScalar(0);</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;            write&lt;StorageIndex, (InputBlockProperties::is_coalesced_layout ? 1 : WorkLoadPerThreadNC),</div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;                  data_source::private_mem&gt;(</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;                val, private_ptr + (InputBlockProperties::is_coalesced_layout ? i : 0) +</div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;                         ((InputBlockProperties::is_coalesced_layout ? 0 : i) * WorkLoadPerThreadNC));</div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;          }</div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;        }</div>
<div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160; </div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;        <span class="comment">// if it is lhs we have to load it packetised when the packet size is &gt; 1, because the output is coalesced. So</span></div>
<div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;        <span class="comment">// even if M is not accessed in a coalesced mode, we have to load packet_size number of m per thread.</span></div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;        ncIndex = (!InputBlockProperties::is_rhs &amp;&amp; InputBlockProperties::nc_stride == 1 &amp;&amp; PacketSize != 1)</div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;                      ? ncOffset + (ncId + 1) % PacketSize + ((ncId + 1) / PacketSize) * LocalThreadSizeNC</div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;                      : (ncIndex + InputBlockProperties::nc_stride * LocalThreadSizeNC);</div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;        private_ptr += InputBlockProperties::nc_stride;</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;      }</div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;      <span class="comment">// the previous for loop ( private_ptr += (ncId * nc_stride)) has already moved ptr with one WorkLoadPerThreadNC</span></div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;      private_ptr += (InputBlockProperties::c_stride - 1) * WorkLoadPerThreadNC;</div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;      cIndex += InputBlockProperties::c_stride;</div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;    }</div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;  }</div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> InputBlockProperties, StorageIndex TileSizeDimNC&gt;</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::pair&lt;StorageIndex, StorageIndex&gt; local_id_extract(</div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;      <span class="keyword">const</span> StorageIndex &amp;linearLocalThreadId) {</div>
<div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;    <span class="keyword">const</span> StorageIndex localThreadNC =</div>
<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;        (InputBlockProperties::is_coalesced_layout)</div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;            ? linearLocalThreadId % (TileSizeDimNC / InputBlockProperties::nc_stride)</div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;            : linearLocalThreadId / (Properties::TileSizeDimK / InputBlockProperties::c_stride);</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;    <span class="keyword">const</span> StorageIndex localThreadC =</div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;        (InputBlockProperties::is_coalesced_layout)</div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;            ? linearLocalThreadId / (TileSizeDimNC / InputBlockProperties::nc_stride)</div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;            : linearLocalThreadId % (Properties::TileSizeDimK / InputBlockProperties::c_stride);</div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;    <span class="keywordflow">return</span> std::pair&lt;StorageIndex, StorageIndex&gt;(localThreadNC, localThreadC);</div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;  }</div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160; </div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> db = Properties::DoubleBuffer, contraction_type ctp = contraction_tp&gt;</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;      std::enable_if_t&lt;db &amp;&amp; ctp == contraction_type::local&gt;</div>
<div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;      sync_mem(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;, <span class="keywordtype">bool</span> &amp;db_offset) noexcept {</div>
<div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;    db_offset = !db_offset;</div>
<div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;  }</div>
<div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160; </div>
<div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> db = Properties::DoubleBuffer, contraction_type ctp = contraction_tp&gt;</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;      std::enable_if_t&lt;!db &amp;&amp; ctp == contraction_type::local&gt;</div>
<div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;      sync_mem(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID, <span class="keywordtype">bool</span> &amp;) noexcept {</div>
<div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;    itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;  }</div>
<div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160; </div>
<div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;  <span class="keyword">template</span> &lt;contraction_type ctp = contraction_tp&gt;</div>
<div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;      std::enable_if_t&lt;ctp == contraction_type::no_local&gt;</div>
<div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;      sync_mem(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;, <span class="keywordtype">bool</span> &amp;) noexcept {</div>
<div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;  }</div>
<div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160; </div>
<div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> need_sync, contraction_type ctp = contraction_tp&gt;</div>
<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;      std::enable_if_t&lt;need_sync &amp;&amp; ctp == contraction_type::no_local&gt;</div>
<div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;      sync_thread(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;</div>
<div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;#ifdef EIGEN_SYCL_ARM_GPU_CACHE_OPTIMISATION</div>
<div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;                      itemID</div>
<div class="line"><a name="l00812"></a><span class="lineno">  812</span>&#160;#endif</div>
<div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;                  ) noexcept {</div>
<div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_ARM_GPU_CACHE_OPTIMISATION</span></div>
<div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;    itemID.barrier(cl::sycl::access::fence_spacce::local_space);</div>
<div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;  }</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> need_sync, contraction_type ctp = contraction_tp&gt;</div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;      std::enable_if_t&lt;need_sync &amp;&amp; ctp == contraction_type::local&gt;</div>
<div class="line"><a name="l00823"></a><span class="lineno">  823</span>&#160;      sync_thread(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID) {</div>
<div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;    itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;  }</div>
<div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> need_sync&gt;</div>
<div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::enable_if_t&lt;!need_sync&gt; sync_thread(</div>
<div class="line"><a name="l00828"></a><span class="lineno">  828</span>&#160;      <span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;) {</div>
<div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00830"></a><span class="lineno">  830</span>&#160;  }</div>
<div class="line"><a name="l00831"></a><span class="lineno">  831</span>&#160; </div>
<div class="line"><a name="l00832"></a><span class="lineno">  832</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_<span class="keywordtype">int</span>ernal_block&gt;</div>
<div class="line"><a name="l00833"></a><span class="lineno">  833</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> compute_tile_per_panel(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID,</div>
<div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;                                                                    ThreadProperties&lt;StorageIndex&gt; &amp;thread_properties,</div>
<div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;                                                                    TiledMemory &amp;tiled_input_block,</div>
<div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160;                                                                    PacketReturnType *privateRes, <span class="keywordtype">bool</span> &amp;db_offset) {</div>
<div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;    <span class="comment">// Tiling the Rhs block from global to local memory</span></div>
<div class="line"><a name="l00838"></a><span class="lineno">  838</span>&#160;    extract_block&lt;RHSBlockProperties, is_internal_block&gt;(</div>
<div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;        rhs, tiled_input_block.rhs_scratch_extract.ptr + (db_offset * Properties::TileSizeDimK * LSDR),</div>
<div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160;        tiled_input_block.rhs_extract_index,</div>
<div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160;        contraction_tp == contraction_type::local ? thread_properties.nGroupOffset : thread_properties.nGlobalOffset,</div>
<div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160;        thread_properties.kGroupOffset - thread_properties.kSize);</div>
<div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160; </div>
<div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;    sync_thread&lt;contraction_tp == contraction_type::no_local&gt;(itemID);</div>
<div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160; </div>
<div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;    <span class="comment">// Tiling the Lhs block from global to local memory</span></div>
<div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;    extract_block&lt;LHSBlockProperties, is_internal_block&gt;(</div>
<div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;        lhs, tiled_input_block.lhs_scratch_extract.ptr + (db_offset * LSDL * Properties::TileSizeDimK),</div>
<div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;        tiled_input_block.lhs_extract_index,</div>
<div class="line"><a name="l00850"></a><span class="lineno">  850</span>&#160;        contraction_tp == contraction_type::local ? thread_properties.mGroupOffset : thread_properties.mGlobalOffset,</div>
<div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160;        thread_properties.kGroupOffset - thread_properties.kSize);</div>
<div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160; </div>
<div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;    <span class="comment">// itemID.barrier(cl::sycl::access::fence_space::local_space);</span></div>
<div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;    sync_thread&lt;contraction_tp == contraction_type::local&gt;(itemID);</div>
<div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;    <span class="comment">// switch to compute mede</span></div>
<div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;    StorageIndex lhs_offset = (db_offset * LSDL * Properties::TileSizeDimK);</div>
<div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;    StorageIndex rhs_offset = (db_offset * Properties::TileSizeDimK * LSDR);</div>
<div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;    <span class="comment">// Loop over the values of a single tile</span></div>
<div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;    <span class="keywordflow">for</span> (StorageIndex k = 0; k &lt; Properties::TileSizeDimK; k++) {</div>
<div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;      compute_block_per_tile(tiled_input_block.lhs_scratch_ptr_compute + lhs_offset,</div>
<div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160;                             tiled_input_block.rhs_scratch_ptr_compute + rhs_offset, privateRes);</div>
<div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;      lhs_offset += LSDL;</div>
<div class="line"><a name="l00863"></a><span class="lineno">  863</span>&#160;      rhs_offset += LSDR;</div>
<div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;    }</div>
<div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160;    <span class="comment">// computing the K index for the next tile</span></div>
<div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;    thread_properties.kSize -= Properties::TileSizeDimK;</div>
<div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;    sync_mem(itemID, db_offset);</div>
<div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;  }</div>
<div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160; </div>
<div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160;  <span class="comment">// when local memory is available the following compute_panel will be enabled</span></div>
<div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_<span class="keywordtype">int</span>ernal_block, <span class="keyword">typename</span> OutPtr&gt;</div>
<div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> compute_panel(<span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID,</div>
<div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;                                                           ThreadProperties&lt;StorageIndex&gt; &amp;thread_properties,</div>
<div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;                                                           OutPtr out_ptr) {</div>
<div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;    <span class="keyword">auto</span> tiled_input_block = TiledMemory{thread_properties, scratch.get_pointer()};</div>
<div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;    <span class="comment">// Allocate register space</span></div>
<div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160;    PacketReturnType privateRes[Properties::WorkLoadPerThreadM * Properties::WorkLoadPerThreadN / PacketSize] = {</div>
<div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;        PacketReturnType{0}};</div>
<div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;    <span class="keywordtype">bool</span> db_offset = 0;</div>
<div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160; </div>
<div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;    <span class="keywordflow">while</span> (thread_properties.kSize &gt;= Properties::TileSizeDimK) {</div>
<div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;      compute_tile_per_panel&lt;is_internal_block&gt;(itemID, thread_properties, tiled_input_block, privateRes, db_offset);</div>
<div class="line"><a name="l00883"></a><span class="lineno">  883</span>&#160;    }</div>
<div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;    <span class="keywordflow">if</span> (thread_properties.kSize &gt; 0) {</div>
<div class="line"><a name="l00885"></a><span class="lineno">  885</span>&#160;      compute_tile_per_panel&lt;false&gt;(itemID, thread_properties, tiled_input_block, privateRes, db_offset);</div>
<div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;    }</div>
<div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160; </div>
<div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;    <span class="comment">// Storing the final results in the output</span></div>
<div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;    store&lt;is_internal_block,</div>
<div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;          contraction_tp == contraction_type::local ? <span class="keyword">static_cast&lt;</span>StorageIndex<span class="keyword">&gt;</span>(1) : RHSBlockProperties::nc_stride&gt;(</div>
<div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;        out_ptr + thread_properties.nGlobalOffset * triple_dim.M, privateRes, thread_properties.mGlobalOffset,</div>
<div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;        thread_properties.nGlobalOffset);</div>
<div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;  }</div>
<div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;  <span class="comment">// When local memory is available the following extract_block will be enabled</span></div>
<div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> InputBlockProperties, <span class="keywordtype">bool</span> is_internal_block, <span class="keyword">typename</span> Input, <span class="keyword">typename</span> Local,</div>
<div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;            contraction_type contract_tp = contraction_tp&gt;</div>
<div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE</div>
<div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;      std::enable_if_t&lt;contract_tp == contraction_type::local&gt;</div>
<div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;      extract_block(<span class="keyword">const</span> Input &amp;inpt, Local local_ptr, <span class="keyword">const</span> std::pair&lt;StorageIndex, StorageIndex&gt;&amp; local_index,</div>
<div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160;                    <span class="keyword">const</span> StorageIndex &amp;ncOffset, <span class="keyword">const</span> StorageIndex cOffset) {</div>
<div class="line"><a name="l00901"></a><span class="lineno">  901</span>&#160;    EIGEN_CONSTEXPR StorageIndex TileSizeDimNC =</div>
<div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;        InputBlockProperties::is_rhs ? Properties::TileSizeDimN : Properties::TileSizeDimM;</div>
<div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160;    EIGEN_CONSTEXPR StorageIndex LoadPerThread =</div>
<div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;        InputBlockProperties::is_rhs ? Properties::LoadPerThreadRhs : Properties::LoadPerThreadLhs;</div>
<div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;    EIGEN_CONSTEXPR StorageIndex LSD = InputBlockProperties::is_rhs ? LSDR : LSDL;</div>
<div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;    static_assert(((LocalOffset % (TileSizeDimNC / InputBlockProperties::nc_stride) == 0) &amp;&amp;</div>
<div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;                   (LocalOffset % (Properties::TileSizeDimK / InputBlockProperties::c_stride) == 0)),</div>
<div class="line"><a name="l00908"></a><span class="lineno">  908</span>&#160;                  <span class="stringliteral">&quot; LocalOffset must be divisable by stride&quot;</span>);</div>
<div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160;    <span class="keyword">const</span> StorageIndex &amp;NC = InputBlockProperties::is_rhs ? triple_dim.N : triple_dim.M;</div>
<div class="line"><a name="l00910"></a><span class="lineno">  910</span>&#160;    StorageIndex localThreadNC = local_index.first;</div>
<div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160;    StorageIndex localThreadC = local_index.second;</div>
<div class="line"><a name="l00912"></a><span class="lineno">  912</span>&#160;    <span class="keyword">auto</span> chk_bound = [&amp;](<span class="keyword">const</span> StorageIndex &amp;CIndex, <span class="keyword">const</span> StorageIndex &amp;NCIndex) EIGEN_DEVICE_FUNC {</div>
<div class="line"><a name="l00913"></a><span class="lineno">  913</span>&#160;      <span class="keywordflow">return</span> ((CIndex + InputBlockProperties::c_stride - 1 &lt; triple_dim.K) &amp;&amp;</div>
<div class="line"><a name="l00914"></a><span class="lineno">  914</span>&#160;              (NCIndex + InputBlockProperties::nc_stride - 1 &lt; NC));</div>
<div class="line"><a name="l00915"></a><span class="lineno">  915</span>&#160;    };</div>
<div class="line"><a name="l00916"></a><span class="lineno">  916</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00917"></a><span class="lineno">  917</span>&#160;    <span class="keywordflow">for</span> (StorageIndex lPT = 0; lPT &lt; LoadPerThread / InputBlockProperties::elements_per_access; lPT++) {</div>
<div class="line"><a name="l00918"></a><span class="lineno">  918</span>&#160;      <span class="keyword">const</span> StorageIndex CIndex = cOffset + (InputBlockProperties::c_stride * localThreadC);</div>
<div class="line"><a name="l00919"></a><span class="lineno">  919</span>&#160;      <span class="keyword">const</span> StorageIndex NCIndex = ncOffset + (InputBlockProperties::nc_stride * localThreadNC);</div>
<div class="line"><a name="l00920"></a><span class="lineno">  920</span>&#160;      <span class="keyword">const</span> StorageIndex ld = InputBlockProperties::is_coalesced_layout ? NC : triple_dim.K;</div>
<div class="line"><a name="l00921"></a><span class="lineno">  921</span>&#160;      <span class="keywordflow">if</span> (check_boundary&lt;is_internal_block&gt;(chk_bound(CIndex, NCIndex))) {</div>
<div class="line"><a name="l00922"></a><span class="lineno">  922</span>&#160;        <span class="keyword">auto</span> val =</div>
<div class="line"><a name="l00923"></a><span class="lineno">  923</span>&#160;            read&lt;InputBlockProperties::packet_load, InputBlockProperties::is_coalesced_layout,</div>
<div class="line"><a name="l00924"></a><span class="lineno">  924</span>&#160;                 InputBlockProperties::is_rhs, <span class="keyword">typename</span> InputBlockProperties::OutType&gt;(inpt, NCIndex, CIndex, ld);</div>
<div class="line"><a name="l00925"></a><span class="lineno">  925</span>&#160;        write&lt;StorageIndex, (InputBlockProperties::is_coalesced_layout ? 1 : LSD), data_source::local_mem&gt;(</div>
<div class="line"><a name="l00926"></a><span class="lineno">  926</span>&#160;            val, local_ptr + (InputBlockProperties::nc_stride * localThreadNC) +</div>
<div class="line"><a name="l00927"></a><span class="lineno">  927</span>&#160;                     (InputBlockProperties::c_stride * localThreadC * LSD));</div>
<div class="line"><a name="l00928"></a><span class="lineno">  928</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00929"></a><span class="lineno">  929</span>&#160;        EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l00930"></a><span class="lineno">  930</span>&#160;        <span class="keywordflow">for</span> (StorageIndex i = 0; i &lt; InputBlockProperties::elements_per_access; i++) {</div>
<div class="line"><a name="l00931"></a><span class="lineno">  931</span>&#160;          <span class="keyword">const</span> StorageIndex nCInd = NCIndex + (InputBlockProperties::is_coalesced_layout ? i : 0);</div>
<div class="line"><a name="l00932"></a><span class="lineno">  932</span>&#160;          <span class="keyword">const</span> StorageIndex cInd = CIndex + (InputBlockProperties::is_coalesced_layout ? 0 : i);</div>
<div class="line"><a name="l00933"></a><span class="lineno">  933</span>&#160;          OutScalar val =</div>
<div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;              (nCInd &lt; NC &amp;&amp; cInd &lt; triple_dim.K)</div>
<div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160;                  ? read&lt;false, InputBlockProperties::is_coalesced_layout, InputBlockProperties::is_rhs, OutScalar&gt;(</div>
<div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;                        inpt, nCInd, cInd, ld)</div>
<div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;                  : OutScalar(0);</div>
<div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160; </div>
<div class="line"><a name="l00939"></a><span class="lineno">  939</span>&#160;          write&lt;StorageIndex, (InputBlockProperties::is_coalesced_layout ? 1 : LSD), data_source::local_mem&gt;(</div>
<div class="line"><a name="l00940"></a><span class="lineno">  940</span>&#160;              val, local_ptr + (InputBlockProperties::nc_stride * localThreadNC) +</div>
<div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;                       (InputBlockProperties::is_coalesced_layout ? i : 0) +</div>
<div class="line"><a name="l00942"></a><span class="lineno">  942</span>&#160;                       ((InputBlockProperties::c_stride * localThreadC +</div>
<div class="line"><a name="l00943"></a><span class="lineno">  943</span>&#160;                         (InputBlockProperties::is_coalesced_layout ? 0 : i)) *</div>
<div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;                        LSD));</div>
<div class="line"><a name="l00945"></a><span class="lineno">  945</span>&#160;        }</div>
<div class="line"><a name="l00946"></a><span class="lineno">  946</span>&#160;      }</div>
<div class="line"><a name="l00947"></a><span class="lineno">  947</span>&#160;      localThreadNC += (InputBlockProperties::is_coalesced_layout)</div>
<div class="line"><a name="l00948"></a><span class="lineno">  948</span>&#160;                           ? LocalOffset % (TileSizeDimNC / InputBlockProperties::nc_stride)</div>
<div class="line"><a name="l00949"></a><span class="lineno">  949</span>&#160;                           : LocalOffset / (Properties::TileSizeDimK / InputBlockProperties::c_stride);</div>
<div class="line"><a name="l00950"></a><span class="lineno">  950</span>&#160;      localThreadC += (InputBlockProperties::is_coalesced_layout)</div>
<div class="line"><a name="l00951"></a><span class="lineno">  951</span>&#160;                          ? LocalOffset / (TileSizeDimNC / InputBlockProperties::nc_stride)</div>
<div class="line"><a name="l00952"></a><span class="lineno">  952</span>&#160;                          : LocalOffset % (Properties::TileSizeDimK / InputBlockProperties::c_stride);</div>
<div class="line"><a name="l00953"></a><span class="lineno">  953</span>&#160;    }</div>
<div class="line"><a name="l00954"></a><span class="lineno">  954</span>&#160;  }</div>
<div class="line"><a name="l00955"></a><span class="lineno">  955</span>&#160;};</div>
<div class="line"><a name="l00956"></a><span class="lineno">  956</span>&#160; </div>
<div class="line"><a name="l00957"></a><span class="lineno">  957</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_GEMV</span></div>
<div class="line"><a name="l00958"></a><span class="lineno">  958</span>&#160; </div>
<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OutScalar, <span class="keyword">typename</span> OutAccessor, <span class="keyword">typename</span> VectorMapper, <span class="keyword">typename</span> TensorMapper, <span class="keyword">typename</span> StorageIndex,</div>
<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160;          <span class="keyword">typename</span> Properties, StorageIndex KFactor, <span class="keywordtype">bool</span> Vectorizable, <span class="keywordtype">bool</span> is_lhs_vec, <span class="keywordtype">bool</span> IsFinal&gt;</div>
<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160;<span class="keyword">struct </span>GeneralVectorTensor {</div>
<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Eigen::TensorSycl::internal::Vectorise&lt;OutScalar, Eigen::SyclDevice, Vectorizable&gt;::PacketReturnType</div>
<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160;      PacketReturnType;</div>
<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">int</span> PacketSize =</div>
<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160;      Eigen::TensorSycl::internal::Vectorise&lt;OutScalar, Eigen::SyclDevice, Vectorizable&gt;::PacketSize;</div>
<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;OutScalar, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt; Scratch;</div>
<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>&#160; </div>
<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>&#160;  <span class="keyword">static</span> EIGEN_CONSTEXPR StorageIndex OutScratchOffset =</div>
<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160;      KFactor * Properties::LocalThreadSizeC * Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160; </div>
<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160;  <span class="comment">// Since the access layout for a vector can always be coalesced, when LHS is a vector, we pass false and false to make</span></div>
<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>&#160;  <span class="comment">// sure that the !^ is true When RHS is a vector, we pass true and true to make sure that the !^ is true.</span></div>
<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160;  <span class="keyword">typedef</span> BlockProperties&lt;is_lhs_vec ? false : true, is_lhs_vec ? false : true, Vectorizable, PacketReturnType&gt;</div>
<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>&#160;      VecBlockProperties;</div>
<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>&#160; </div>
<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>&#160;  Scratch scratch;</div>
<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>&#160;  <span class="keyword">const</span> VectorMapper vec;</div>
<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160;  <span class="keyword">const</span> TensorMapper mat;</div>
<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160;  OutAccessor out_res;</div>
<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160;  <span class="keyword">const</span> StorageIndex nonContractGroupSize;</div>
<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160;  <span class="keyword">const</span> StorageIndex nonContractDim;</div>
<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>&#160;  <span class="keyword">const</span> StorageIndex contractDim;</div>
<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160; </div>
<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE GeneralVectorTensor(Scratch scratch_, <span class="keyword">const</span> VectorMapper vec_,</div>
<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160;                                                            <span class="keyword">const</span> TensorMapper mat_, OutAccessor out_res_,</div>
<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160;                                                            <span class="keyword">const</span> StorageIndex nonContractGroupSize_,</div>
<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160;                                                            <span class="keyword">const</span> StorageIndex nonContractDim_,</div>
<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160;                                                            <span class="keyword">const</span> StorageIndex contractDim_)</div>
<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160;      : scratch(scratch_),</div>
<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160;        vec(vec_),</div>
<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>&#160;        mat(mat_),</div>
<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>&#160;        out_res(out_res_),</div>
<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;        nonContractGroupSize(nonContractGroupSize_),</div>
<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160;        nonContractDim(nonContractDim_),</div>
<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160;        contractDim(contractDim_) {}</div>
<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160; </div>
<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160;    <span class="keyword">auto</span> scratch_ptr = scratch.get_pointer();</div>
<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160;    <span class="keyword">const</span> StorageIndex linearLocalThreadId = itemID.get_local_id(0);</div>
<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160;    StorageIndex nonContractId = is_lhs_vec ? linearLocalThreadId / Properties::LocalThreadSizeC</div>
<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160;                                            : linearLocalThreadId % Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;    StorageIndex contractId = is_lhs_vec ? linearLocalThreadId % Properties::LocalThreadSizeC</div>
<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160;                                         : linearLocalThreadId / Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160;    <span class="keyword">const</span> StorageIndex cGroupSize = itemID.get_group_range(0) / nonContractGroupSize;</div>
<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160;    <span class="keyword">const</span> StorageIndex nonContractGroupId =</div>
<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160;        is_lhs_vec ? itemID.get_group(0) / cGroupSize : itemID.get_group(0) % nonContractGroupSize;</div>
<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160;    <span class="keyword">const</span> StorageIndex contractGroupId =</div>
<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160;        is_lhs_vec ? itemID.get_group(0) % cGroupSize : itemID.get_group(0) / nonContractGroupSize;</div>
<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160;    <span class="keyword">auto</span> out_ptr = out_res.get_pointer() + (IsFinal ? 0 : contractGroupId * nonContractDim);</div>
<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160; </div>
<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160;    <span class="keyword">const</span> StorageIndex nonContractGroupOffset = nonContractGroupId * Properties::TileSizeDimNC;</div>
<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160;    <span class="keyword">const</span> StorageIndex contractGroupOffset = contractGroupId * Properties::TileSizeDimC;</div>
<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160;    <span class="keyword">auto</span> outScratchIndex = nonContractId + contractId * Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160;    <span class="keyword">const</span> StorageIndex globalNonContractDimOffset = nonContractGroupOffset + nonContractId;</div>
<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160;    <span class="keyword">const</span> StorageIndex globalContractDimOffset = contractGroupOffset + contractId;</div>
<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160;    <span class="keyword">auto</span> local_output = scratch_ptr + OutScratchOffset;</div>
<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> is_internal = nonContractDim - nonContractGroupOffset &gt;= Properties::TileSizeDimNC &amp;&amp;</div>
<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>&#160;                             contractDim - contractGroupOffset &gt;= Properties::TileSizeDimC;</div>
<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160;    is_internal</div>
<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>&#160;        ? compute_panel&lt;true&gt;(itemID, vec, mat, local_output, out_ptr,</div>
<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>&#160;#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</div>
<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160;                              scratch_ptr, contractGroupOffset,</div>
<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>&#160;#endif</div>
<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160;                              nonContractGroupOffset, linearLocalThreadId, contractDim, nonContractDim, contractId,</div>
<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160;                              nonContractId, globalContractDimOffset, globalNonContractDimOffset, outScratchIndex)</div>
<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160;        : compute_panel&lt;false&gt;(itemID, vec, mat, local_output, out_ptr,</div>
<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</div>
<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160;                               scratch_ptr, contractGroupOffset,</div>
<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;#endif</div>
<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160;                               nonContractGroupOffset, linearLocalThreadId, contractDim, nonContractDim, contractId,</div>
<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;                               nonContractId, globalContractDimOffset, globalNonContractDimOffset, outScratchIndex);</div>
<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;  }</div>
<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_<span class="keywordtype">int</span>ernal_block, <span class="keyword">typename</span> OutPtr&gt;</div>
<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> compute_panel(</div>
<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160;      <span class="keyword">const</span> cl::sycl::nd_item&lt;1&gt; &amp;itemID, <span class="keyword">const</span> VectorMapper &amp;vec, <span class="keyword">const</span> TensorMapper &amp;mat, OutScalar *local_output,</div>
<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;      OutPtr out_ptr,</div>
<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</div>
<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;      OutScalar *scratch_ptr, <span class="keyword">const</span> StorageIndex contractGroupOffset,</div>
<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160;#endif</div>
<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160;      <span class="keyword">const</span> StorageIndex nonContractGroupOffset, <span class="keyword">const</span> StorageIndex linearLocalThreadId, StorageIndex contractDim,</div>
<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160;      StorageIndex nonContractDim, StorageIndex contractId, StorageIndex nonContractId,</div>
<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160;      StorageIndex globalContractDimOffset, StorageIndex globalNonContractDimOffset, StorageIndex outScratchIndex) {</div>
<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160;    OutScalar outScalar[Properties::WorkLoadPerThreadNC] = {OutScalar(0)};</div>
<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160;    <span class="comment">// Reading the vector</span></div>
<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</span></div>
<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160;    <span class="keyword">const</span> StorageIndex vectorOffset = contractGroupOffset + linearLocalThreadId;</div>
<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>&#160;    extract_block&lt;VecBlockProperties, is_internal_block, KFactor,</div>
<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>&#160;                  Properties::LocalThreadSizeNC * Properties::LocalThreadSizeC&gt;(vec, scratch_ptr, linearLocalThreadId,</div>
<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>&#160;                                                                                vectorOffset, contractDim);</div>
<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160; </div>
<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>&#160;    itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160;    <span class="keyword">auto</span> in_scratch_ptr = scratch_ptr + contractId;</div>
<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160; </div>
<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160;    StorageIndex privateOffsetC = 0;</div>
<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160;    <span class="keywordflow">for</span> (StorageIndex i = 0; i &lt; Properties::WorkLoadPerThreadC; i++) {</div>
<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160;      StorageIndex privateOffsetNC = 0;</div>
<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160;      <span class="keywordtype">bool</span> contract_conds = ((globalContractDimOffset + privateOffsetC) &lt; contractDim);</div>
<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</span></div>
<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160;      <span class="keyword">auto</span> vecScalar = *in_scratch_ptr;</div>
<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>&#160;      <span class="keyword">auto</span> vecScalar = (check_boundary&lt;is_internal_block&gt;(contract_conds))</div>
<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>&#160;                           ? vec(is_lhs_vec ? StorageIndex(0) : globalContractDimOffset + privateOffsetC,</div>
<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>&#160;                                 is_lhs_vec ? globalContractDimOffset + privateOffsetC : StorageIndex(0))</div>
<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>&#160;                           : OutScalar(0);</div>
<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>&#160;      <span class="keywordflow">for</span> (StorageIndex j = 0; j &lt; Properties::WorkLoadPerThreadNC; j++) {</div>
<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>&#160;        <span class="keyword">auto</span> matScalar = (check_boundary&lt;is_internal_block&gt;(</div>
<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>&#160;                             contract_conds &amp;&amp; ((globalNonContractDimOffset + privateOffsetNC) &lt; nonContractDim)))</div>
<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>&#160;                             ? mat(is_lhs_vec ? globalContractDimOffset + privateOffsetC</div>
<div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>&#160;                                              : globalNonContractDimOffset + privateOffsetNC,</div>
<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>&#160;                                   is_lhs_vec ? globalNonContractDimOffset + privateOffsetNC</div>
<div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>&#160;                                              : globalContractDimOffset + privateOffsetC)</div>
<div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>&#160;                             : OutScalar(0);</div>
<div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>&#160; </div>
<div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>&#160;        outScalar[j] = cl::sycl::mad(matScalar, vecScalar, outScalar[j]);</div>
<div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>&#160;        privateOffsetNC += Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>&#160;      }</div>
<div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>&#160;      privateOffsetC += Properties::LocalThreadSizeC;</div>
<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</span></div>
<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>&#160;      in_scratch_ptr += Properties::LocalThreadSizeC;</div>
<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160;    }</div>
<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160; </div>
<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160;    <span class="keyword">auto</span> out_scratch_ptr = local_output + outScratchIndex;</div>
<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160;    <span class="comment">// Each block of 16*16 element in shared memory should reduce to 16*1</span></div>
<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>&#160;    <span class="keywordflow">for</span> (StorageIndex j = 0; j &lt; Properties::WorkLoadPerThreadNC; j++) {</div>
<div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>&#160;      *out_scratch_ptr = outScalar[j];</div>
<div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>&#160; </div>
<div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>&#160;      out_scratch_ptr += (Properties::LocalThreadSizeNC * Properties::LocalThreadSizeC);</div>
<div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>&#160;    }</div>
<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>&#160;    <span class="keywordflow">if</span> (is_lhs_vec) {</div>
<div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>&#160;      nonContractId = linearLocalThreadId % Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>&#160;      contractId = linearLocalThreadId / Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>&#160;      outScratchIndex = nonContractId + contractId * Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>&#160;    }</div>
<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>&#160; </div>
<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>&#160;    out_scratch_ptr = local_output + outScratchIndex;</div>
<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>&#160;    EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>&#160;    <span class="keywordflow">for</span> (StorageIndex j = 0; j &lt; Properties::WorkLoadPerThreadNC; j++) {</div>
<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>&#160;      <span class="keywordflow">for</span> (StorageIndex offset = Properties::LocalThreadSizeC &gt;&gt; 1; offset &gt; 0; offset &gt;&gt;= 1) {</div>
<div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>&#160;        itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>&#160;        <span class="keywordflow">if</span> (contractId &lt; offset) {</div>
<div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>&#160;          StorageIndex myNeigbourId = (Properties::LocalThreadSizeNC * offset);</div>
<div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>&#160;          *out_scratch_ptr += out_scratch_ptr[myNeigbourId];</div>
<div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>&#160;        }</div>
<div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>&#160;      }</div>
<div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>&#160;      <span class="comment">// moving to next 16 by 16 block</span></div>
<div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>&#160;      out_scratch_ptr += (Properties::LocalThreadSizeNC * Properties::LocalThreadSizeC);</div>
<div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>&#160;    }</div>
<div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>&#160; </div>
<div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>&#160;    <span class="keywordflow">if</span> (contractId == 0) {</div>
<div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>&#160;      out_scratch_ptr = local_output + nonContractId;</div>
<div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>&#160;      StorageIndex global_final_offset = nonContractGroupOffset + nonContractId;</div>
<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>&#160;      out_ptr += global_final_offset;</div>
<div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>&#160;      EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>&#160;      <span class="keywordflow">for</span> (StorageIndex j = 0; j &lt; Properties::WorkLoadPerThreadNC; j++) {</div>
<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>&#160;        <span class="keywordflow">if</span> (check_boundary&lt;is_internal_block&gt;(global_final_offset &lt; nonContractDim)) {</div>
<div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>&#160;          <span class="keyword">auto</span> res = *out_scratch_ptr;</div>
<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>&#160; </div>
<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>&#160;          *out_ptr = res;</div>
<div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>&#160;          out_ptr += Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>&#160;        }</div>
<div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>&#160;        <span class="comment">// moving to next 16 by 16 block to ge the next 16 reduced elements</span></div>
<div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>&#160;        out_scratch_ptr += (Properties::LocalThreadSizeNC * Properties::LocalThreadSizeC);</div>
<div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>&#160;        <span class="keywordflow">if</span> (!(is_internal_block)) global_final_offset += Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>&#160;      }</div>
<div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>&#160;    }</div>
<div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>&#160;  }</div>
<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>&#160; </div>
<div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> InputBlockProperties, <span class="keywordtype">bool</span> is_internal_block, <span class="keywordtype">int</span> CFactor, <span class="keywordtype">int</span> GroupSize, <span class="keyword">typename</span> Input,</div>
<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>&#160;            <span class="keyword">typename</span> Local&gt;</div>
<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>&#160;  <span class="keyword">static</span> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> extract_block(<span class="keyword">const</span> Input &amp;inpt, Local *local_ptr,</div>
<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>&#160;                                                                  <span class="keyword">const</span> StorageIndex &amp;linearLocalThreadId,</div>
<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>&#160;                                                                  <span class="keyword">const</span> StorageIndex &amp;cOffset, <span class="keyword">const</span> StorageIndex &amp;C) {</div>
<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>&#160;    local_ptr += InputBlockProperties::c_stride * linearLocalThreadId;</div>
<div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>&#160;    StorageIndex cIndex = cOffset;</div>
<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>&#160;    <span class="keywordflow">for</span> (StorageIndex cId = 0; cId &lt; CFactor / InputBlockProperties::c_stride; cId++) {</div>
<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>&#160;      <span class="keywordflow">if</span> (check_boundary&lt;is_internal_block&gt;(cIndex + InputBlockProperties::c_stride - 1 &lt; C)) {</div>
<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>&#160;        <span class="keyword">auto</span> val = read&lt;InputBlockProperties::packet_load, InputBlockProperties::is_coalesced_layout,</div>
<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>&#160;                        InputBlockProperties::is_rhs, <span class="keyword">typename</span> InputBlockProperties::OutType&gt;(inpt, StorageIndex(0),</div>
<div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>&#160;                                                                                              cIndex, StorageIndex(1));</div>
<div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>&#160;        write&lt;StorageIndex, 1, data_source::local_mem&gt;(val, local_ptr);</div>
<div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>&#160;        EIGEN_UNROLL_LOOP</div>
<div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>&#160;        <span class="keywordflow">for</span> (StorageIndex i = 0; i &lt; InputBlockProperties::elements_per_access; i++) {</div>
<div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>&#160;          OutScalar val =</div>
<div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>&#160;              (cIndex + i &lt; C)</div>
<div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>&#160;                  ? read&lt;false, InputBlockProperties::is_coalesced_layout, InputBlockProperties::is_rhs, OutScalar&gt;(</div>
<div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>&#160;                        inpt, StorageIndex(0), cIndex + i, StorageIndex(1))</div>
<div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>&#160;                  : OutScalar(0);</div>
<div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>&#160;          write&lt;StorageIndex, 1, data_source::local_mem&gt;(val, local_ptr + i);</div>
<div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>&#160;        }</div>
<div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>&#160;      }</div>
<div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>&#160;      local_ptr += InputBlockProperties::c_stride * GroupSize;</div>
<div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>&#160;      cIndex += InputBlockProperties::c_stride * GroupSize;</div>
<div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>&#160;    }</div>
<div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>&#160;  }</div>
<div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>&#160;};</div>
<div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>&#160; </div>
<div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_SCALAR</span></div>
<div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>&#160; </div>
<div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OutScalar, <span class="keyword">typename</span> LhsScalar, <span class="keyword">typename</span> RhsScalar, <span class="keyword">typename</span> OutAccessor, <span class="keyword">typename</span> LhsMapper,</div>
<div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>&#160;          <span class="keyword">typename</span> RhsMapper, <span class="keyword">typename</span> StorageIndex, <span class="keywordtype">bool</span> Vectorizable&gt;</div>
<div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>&#160;<span class="keyword">struct </span>GeneralScalarContraction {</div>
<div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>&#160;  <span class="keyword">typedef</span> cl::sycl::accessor&lt;OutScalar, 1, cl::sycl::access::mode::read_write, cl::sycl::access::target::local&gt; Scratch;</div>
<div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>&#160;  Scratch scratch;</div>
<div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>&#160;  <span class="keyword">const</span> LhsMapper lhs;</div>
<div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>&#160;  <span class="keyword">const</span> RhsMapper rhs;</div>
<div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>&#160;  OutAccessor out_res;</div>
<div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>&#160;  <span class="keyword">const</span> StorageIndex rng;</div>
<div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>&#160; </div>
<div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>&#160;  EIGEN_DEVICE_FUNC</div>
<div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>&#160;  GeneralScalarContraction(Scratch scratch_, <span class="keyword">const</span> LhsMapper lhs_, <span class="keyword">const</span> RhsMapper rhs_, OutAccessor out_res_,</div>
<div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>&#160;                           <span class="keyword">const</span> StorageIndex rng_)</div>
<div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>&#160;      : scratch(scratch_), lhs(lhs_), rhs(rhs_), out_res(out_res_), rng(rng_) {}</div>
<div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>&#160; </div>
<div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>&#160;  EIGEN_DEVICE_FUNC <span class="keywordtype">void</span> operator()(cl::sycl::nd_item&lt;1&gt; itemID) {</div>
<div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>&#160;    <span class="keyword">auto</span> out_ptr = out_res.get_pointer();</div>
<div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>&#160;    <span class="keyword">auto</span> scratch_ptr = scratch.get_pointer().get();</div>
<div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>&#160; </div>
<div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>&#160;    StorageIndex globalid = itemID.get_global_id(0);</div>
<div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>&#160;    StorageIndex localid = itemID.get_local_id(0);</div>
<div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>&#160;    OutScalar accumulator = OutScalar(0);</div>
<div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>&#160;    <span class="keywordflow">for</span> (StorageIndex i = globalid; i &lt; rng; i += itemID.get_global_range(0)) {</div>
<div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>&#160;      accumulator = cl::sycl::mad(lhs(0, i), rhs(i, 0), accumulator);</div>
<div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>&#160;    }</div>
<div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>&#160;    <span class="keyword">auto</span> out_scratch_ptr = scratch_ptr + localid;</div>
<div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>&#160;    *out_scratch_ptr = accumulator;</div>
<div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>&#160;    <span class="keywordflow">for</span> (StorageIndex offset = itemID.get_local_range(0) &gt;&gt; 1; offset &gt; 0; offset &gt;&gt;= 1) {</div>
<div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>&#160;      itemID.barrier(cl::sycl::access::fence_space::local_space);</div>
<div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>&#160;      <span class="keywordflow">if</span> (localid &lt; offset) {</div>
<div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>&#160;        *out_scratch_ptr = (accumulator += out_scratch_ptr[offset]);</div>
<div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>&#160;      }</div>
<div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>&#160;    }</div>
<div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>&#160;    <span class="keywordflow">if</span> (localid == 0) {</div>
<div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>&#160;      out_ptr[itemID.get_group(0)] = accumulator;</div>
<div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>&#160;    }</div>
<div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>&#160;  }</div>
<div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>&#160;};</div>
<div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>&#160; </div>
<div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>&#160;}  <span class="comment">// namespace internal</span></div>
<div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>&#160;}  <span class="comment">// namespace TensorSycl</span></div>
<div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>&#160; </div>
<div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Indices, <span class="keyword">typename</span> LeftArgType, <span class="keyword">typename</span> RightArgType, <span class="keyword">typename</span> OutputKernelType&gt;</div>
<div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>&#160;<span class="keyword">struct </span>TensorEvaluator&lt;const TensorContractionOp&lt;Indices, LeftArgType, RightArgType, OutputKernelType&gt;,</div>
<div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>&#160;                       <a class="code" href="namespaceEigen.html">Eigen</a>::SyclDevice&gt;</div>
<div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>&#160;    : <span class="keyword">public</span> TensorContractionEvaluatorBase&lt;TensorEvaluator&lt;</div>
<div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>&#160;          const TensorContractionOp&lt;Indices, LeftArgType, RightArgType, OutputKernelType&gt;, Eigen::SyclDevice&gt;&gt; {</div>
<div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>&#160;  static_assert(std::is_same&lt;OutputKernelType, const NoOpOutputKernel&gt;::value,</div>
<div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>&#160;                <span class="stringliteral">&quot;SYCL tensor contraction does not support output kernels.&quot;</span>);</div>
<div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>&#160; </div>
<div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>&#160;  <span class="keyword">typedef</span> Eigen::SyclDevice Device;</div>
<div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>&#160; </div>
<div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>&#160;  <span class="keyword">typedef</span> TensorEvaluator&lt;const TensorContractionOp&lt;Indices, LeftArgType, RightArgType, OutputKernelType&gt;, Device&gt; Self;</div>
<div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>&#160;  <span class="keyword">typedef</span> TensorContractionEvaluatorBase&lt;Self&gt; Base;</div>
<div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>&#160;  <span class="keyword">typedef</span> TensorContractionOp&lt;Indices, LeftArgType, RightArgType, OutputKernelType&gt; XprType;</div>
<div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>&#160;  <span class="keyword">typedef</span> std::remove_const_t&lt;typename XprType::Scalar&gt; Scalar;</div>
<div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::Index StorageIndex;</div>
<div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> XprType::CoeffReturnType CoeffReturnType;</div>
<div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> PacketType&lt;CoeffReturnType, Device&gt;::type PacketReturnType;</div>
<div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Base::Storage Storage;</div>
<div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> Base::EvaluatorPointerType EvaluatorPointerType;</div>
<div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>&#160;  <span class="keyword">struct </span>TripleDim {</div>
<div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>&#160;    <span class="keyword">const</span> StorageIndex M;</div>
<div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>&#160;    <span class="keyword">const</span> StorageIndex N;</div>
<div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>&#160;    <span class="keyword">const</span> StorageIndex K;</div>
<div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>&#160;    TripleDim(<span class="keyword">const</span> StorageIndex M_, <span class="keyword">const</span> StorageIndex N_, <span class="keyword">const</span> StorageIndex K_) : M(M_), N(N_), K(K_) {}</div>
<div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>&#160;  };</div>
<div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>&#160;  <span class="keyword">enum</span> {</div>
<div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>&#160;    PacketAccess = (PacketType&lt;CoeffReturnType, Device&gt;::size &gt; 1),</div>
<div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>&#160;    BlockAccess = <span class="keyword">false</span>,</div>
<div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>&#160;  };</div>
<div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>&#160; </div>
<div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> Layout = TensorEvaluator&lt;LeftArgType, Device&gt;::Layout;</div>
<div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> LDims = Base::LDims;</div>
<div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> RDims = Base::RDims;</div>
<div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> ContractDims = Base::ContractDims;</div>
<div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>&#160; </div>
<div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>&#160;  <span class="keyword">typedef</span> array&lt;StorageIndex, LDims&gt; left_dim_mapper_t;</div>
<div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>&#160;  <span class="keyword">typedef</span> array&lt;StorageIndex, RDims&gt; right_dim_mapper_t;</div>
<div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>&#160; </div>
<div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>&#160;  <span class="keyword">typedef</span> array&lt;StorageIndex, ContractDims&gt; contract_t;</div>
<div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>&#160;  <span class="keyword">typedef</span> array&lt;StorageIndex, LDims - ContractDims&gt; left_nocontract_t;</div>
<div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>&#160;  <span class="keyword">typedef</span> array&lt;StorageIndex, RDims - ContractDims&gt; right_nocontract_t;</div>
<div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>&#160; </div>
<div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> NumDims = LDims + RDims - 2 * ContractDims;</div>
<div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>&#160; </div>
<div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>&#160;  <span class="keyword">typedef</span> DSizes&lt;StorageIndex, NumDims&gt; Dimensions;</div>
<div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>&#160; </div>
<div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>&#160;  <span class="keyword">typedef</span> TensorEvaluator&lt;typename Base::EvalLeftArgType, Device&gt; LeftEvaluator;</div>
<div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>&#160;  <span class="keyword">typedef</span> TensorEvaluator&lt;typename Base::EvalRightArgType, Device&gt; RightEvaluator;</div>
<div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>&#160;  <span class="keyword">typedef</span> std::remove_const_t&lt;typename LeftEvaluator::CoeffReturnType&gt; LhsScalar;</div>
<div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>&#160;  <span class="keyword">typedef</span> std::remove_const_t&lt;typename RightEvaluator::CoeffReturnType&gt; RhsScalar;</div>
<div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>&#160; </div>
<div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> LeftEvaluator::Dimensions LeftDimensions;</div>
<div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>&#160;  <span class="keyword">typedef</span> <span class="keyword">typename</span> RightEvaluator::Dimensions RightDimensions;</div>
<div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>&#160; </div>
<div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> lhs_inner_dim_contiguous, <span class="keywordtype">bool</span> rhs_inner_dim_contiguous, <span class="keywordtype">bool</span> rhs_inner_dim_reordered&gt;</div>
<div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>&#160;  <span class="keyword">struct </span>input_mapper_propertis {</div>
<div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>&#160;    <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_lhs_matrix = (LDims == 2 &amp;&amp; ContractDims == 1) || lhs_inner_dim_contiguous;</div>
<div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>&#160;    <span class="keyword">static</span> EIGEN_CONSTEXPR <span class="keywordtype">bool</span> is_rhs_matrix =</div>
<div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>&#160;        (RDims == 2 &amp;&amp; ContractDims == 1) || (rhs_inner_dim_contiguous &amp;&amp; !rhs_inner_dim_reordered);</div>
<div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>&#160;  };</div>
<div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>&#160; </div>
<div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>&#160;  TensorEvaluator(<span class="keyword">const</span> XprType &amp;op, <span class="keyword">const</span> Device &amp;device) : Base(op, device) {}</div>
<div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>&#160; </div>
<div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>&#160;  <span class="comment">// We need to redefine this method to make nvcc happy</span></div>
<div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>&#160;  EIGEN_STRONG_INLINE <span class="keywordtype">bool</span> evalSubExprsIfNeeded(<span class="keyword">typename</span> Base::EvaluatorPointerType data) {</div>
<div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>&#160;    this-&gt;m_leftImpl.evalSubExprsIfNeeded(NULL);</div>
<div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>&#160;    this-&gt;m_rightImpl.evalSubExprsIfNeeded(NULL);</div>
<div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>&#160;    <span class="keywordflow">if</span> (!data) {</div>
<div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>&#160;      this-&gt;m_result = this-&gt;m_device.get(</div>
<div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>&#160;          <span class="keyword">static_cast&lt;</span>Scalar *<span class="keyword">&gt;</span>(this-&gt;m_device.allocate_temp(this-&gt;dimensions().TotalSize() * <span class="keyword">sizeof</span>(Scalar))));</div>
<div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>&#160;      data = this-&gt;m_result;</div>
<div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>&#160;    }</div>
<div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>&#160;    evalToSycl(data);</div>
<div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>&#160;    <span class="keywordflow">return</span> (this-&gt;m_result != NULL);</div>
<div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>&#160;  }</div>
<div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>&#160;  <span class="keyword">const</span> Eigen::SyclDevice &amp;device()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> this-&gt;m_device; }</div>
<div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>&#160;  <span class="keywordtype">void</span> evalToSycl(<span class="keyword">typename</span> Base::EvaluatorPointerType buffer)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>&#160;    <span class="keywordflow">if</span> (this-&gt;m_lhs_inner_dim_contiguous) {</div>
<div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>&#160;      <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_contiguous) {</div>
<div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>&#160;        <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_reordered) {</div>
<div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>&#160;          evalTyped&lt;true, true, true, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>&#160;          evalTyped&lt;true, true, false, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>&#160;        }</div>
<div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>&#160;        <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_reordered) {</div>
<div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>&#160;          evalTyped&lt;true, false, true, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160;          evalTyped&lt;true, false, false, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>&#160;        }</div>
<div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>&#160;      }</div>
<div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>&#160;      <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_contiguous) {</div>
<div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>&#160;        <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_reordered) {</div>
<div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>&#160;          evalTyped&lt;false, true, true, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>&#160;          evalTyped&lt;false, true, false, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>&#160;        }</div>
<div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>&#160;        <span class="keywordflow">if</span> (this-&gt;m_rhs_inner_dim_reordered) {</div>
<div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>&#160;          evalTyped&lt;false, false, true, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>&#160;          evalTyped&lt;false, false, false, Unaligned&gt;(buffer);</div>
<div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>&#160;        }</div>
<div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160;      }</div>
<div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>&#160;    }</div>
<div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>&#160;  }</div>
<div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160; </div>
<div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> lhs_inner_dim_contiguous, <span class="keywordtype">bool</span> rhs_inner_dim_contiguous, <span class="keywordtype">bool</span> rhs_inner_dim_reordered, <span class="keywordtype">int</span> Alignment&gt;</div>
<div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160;  <span class="keywordtype">void</span> evalTyped(<span class="keyword">typename</span> Base::EvaluatorPointerType buffer)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160;    <span class="keyword">const</span> <span class="keyword">auto</span> triple_dim = TripleDim{this-&gt;m_i_size, this-&gt;m_j_size, this-&gt;m_k_size};</div>
<div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160;    <span class="keyword">typedef</span> internal::TensorContractionInputMapper&lt;</div>
<div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160;        LhsScalar, StorageIndex, internal::Lhs, LeftEvaluator, left_nocontract_t, contract_t,</div>
<div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160;        PacketType&lt;CoeffReturnType, Device&gt;::size, lhs_inner_dim_contiguous, <span class="keyword">false</span>, <a class="codeRef" href="../group__enums.html#gga45fe06e29902b7a2773de05ba27b47a1a4e19dd09d5ff42295ba1d72d12a46686">Unaligned</a>, MakeSYCLPointer&gt;</div>
<div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160;        LhsMapper;</div>
<div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>&#160; </div>
<div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>&#160;    <span class="keyword">typedef</span> internal::TensorContractionInputMapper&lt;RhsScalar, StorageIndex, internal::Rhs, RightEvaluator,</div>
<div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>&#160;                                                   right_nocontract_t, contract_t,</div>
<div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>&#160;                                                   PacketType&lt;CoeffReturnType, Device&gt;::size, rhs_inner_dim_contiguous,</div>
<div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>&#160;                                                   rhs_inner_dim_reordered, <a class="codeRef" href="../group__enums.html#gga45fe06e29902b7a2773de05ba27b47a1a4e19dd09d5ff42295ba1d72d12a46686">Unaligned</a>, MakeSYCLPointer&gt;</div>
<div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>&#160;        RhsMapper;</div>
<div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>&#160; </div>
<div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>&#160;    <span class="comment">// initialize data mappers</span></div>
<div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160;    LhsMapper lhs(this-&gt;m_leftImpl, this-&gt;m_left_nocontract_strides, this-&gt;m_i_strides,</div>
<div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>&#160;                  this-&gt;m_left_contracting_strides, this-&gt;m_k_strides);</div>
<div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>&#160; </div>
<div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>&#160;    RhsMapper rhs(this-&gt;m_rightImpl, this-&gt;m_right_nocontract_strides, this-&gt;m_j_strides,</div>
<div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>&#160;                  this-&gt;m_right_contracting_strides, this-&gt;m_k_strides);</div>
<div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>&#160; </div>
<div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_SCALAR</span></div>
<div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160;    <span class="keywordflow">if</span> (triple_dim.M == 1 &amp;&amp; triple_dim.N == 1) {</div>
<div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160;      launchSC(buffer, lhs, rhs, triple_dim.K);</div>
<div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160;    } <span class="keywordflow">else</span></div>
<div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_GEMV</span></div>
<div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160;        <span class="keywordflow">if</span> (triple_dim.M != 1 &amp;&amp; triple_dim.N == 1) {</div>
<div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160;      LaunchVT&lt;false&gt;(buffer, rhs, lhs, triple_dim.M, triple_dim.K);</div>
<div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160;    } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (triple_dim.M == 1 &amp;&amp; triple_dim.N != 1) {</div>
<div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;      LaunchVT&lt;true&gt;(buffer, lhs, rhs, triple_dim.N, triple_dim.K);</div>
<div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160;    } <span class="keywordflow">else</span>  <span class="comment">// This is equivalent of if (m!=1 &amp;&amp; n!=1)</span></div>
<div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160;    {</div>
<div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>&#160;      <span class="keyword">typedef</span> input_mapper_propertis&lt;lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered&gt;</div>
<div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160;          inpt_mapper_properties;</div>
<div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_SKINNY</span></div>
<div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160;      <span class="keywordtype">bool</span> skinny = <span class="keyword">false</span>;</div>
<div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>&#160;      <span class="keyword">auto</span> platform_name = this-&gt;device().getPlatformName();</div>
<div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160;      <span class="comment">// This is based on empirical calculation for AMD r9-nano and Fiji</span></div>
<div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160;      <span class="keywordflow">if</span> (platform_name.find(<span class="stringliteral">&quot;AMD&quot;</span>) == 0) {</div>
<div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>&#160;        skinny = (triple_dim.M &lt; triple_dim.K || triple_dim.N &lt; triple_dim.K) &amp;&amp;</div>
<div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>&#160;                 ((triple_dim.M &lt; 1024 &amp;&amp; triple_dim.N &lt; 1024) ||</div>
<div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>&#160;                  (uint64_t(triple_dim.M * triple_dim.N) &lt; uint64_t(triple_dim.K)));</div>
<div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>&#160;        skinny = (((std::max(triple_dim.K, triple_dim.N) / std::min(triple_dim.K, triple_dim.N)) &gt; 100) ||</div>
<div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>&#160;                  ((std::max(triple_dim.K, triple_dim.M) / std::min(triple_dim.K, triple_dim.M)) &gt; 100) ||</div>
<div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>&#160;                  ((std::max(triple_dim.N, triple_dim.M) / std::min(triple_dim.N, triple_dim.M)) &gt; 100));</div>
<div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>&#160;      }</div>
<div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>&#160;      <span class="keywordflow">if</span> (skinny)</div>
<div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>&#160;        adjustTT&lt;true, inpt_mapper_properties&gt;(buffer, lhs, rhs, triple_dim);</div>
<div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>&#160;      <span class="keywordflow">else</span></div>
<div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>&#160;<span class="preprocessor">#endif  </span><span class="comment">// EIGEN_SYCL_DISABLE_SKINNY</span></div>
<div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>&#160;        adjustTT&lt;false, inpt_mapper_properties&gt;(buffer, lhs, rhs, triple_dim);</div>
<div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>&#160;    }</div>
<div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>&#160;  }</div>
<div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>&#160; </div>
<div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> skinny, <span class="keyword">typename</span> input_mapper_properties, <span class="keyword">typename</span> LhsMapper, <span class="keyword">typename</span> RhsMapper&gt;</div>
<div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>&#160;  <span class="keywordtype">void</span> EIGEN_ALWAYS_INLINE adjustTT(EvaluatorPointerType buffer, <span class="keyword">const</span> LhsMapper &amp;lhs, <span class="keyword">const</span> RhsMapper &amp;rhs,</div>
<div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>&#160;                                    <span class="keyword">const</span> TripleDim &amp;triple_dim)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_ON</span></div>
<div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>&#160;    <span class="keywordflow">if</span> (device().has_local_memory()) {</div>
<div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::TTPanelSize&lt;CoeffReturnType, StorageIndex, 4, 4, 16&gt; PanelParameters;</div>
<div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>&#160;      launchTT&lt;TensorSycl::internal::contraction_type::local, skinny, input_mapper_properties, PanelParameters&gt;(</div>
<div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>&#160;          buffer, lhs, rhs, triple_dim);</div>
<div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>&#160;    }</div>
<div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>&#160;<span class="preprocessor">#ifdef EIGEN_SYCL_LOCAL_MEM_UNSET_OR_OFF</span></div>
<div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>&#160;    <span class="keywordflow">if</span> (!(device().has_local_memory())) {</div>
<div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::TTPanelSize&lt;CoeffReturnType, StorageIndex, 4, 4, 4&gt; PanelParameters;</div>
<div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160;      launchTT&lt;TensorSycl::internal::contraction_type::no_local, skinny, input_mapper_properties, PanelParameters&gt;(</div>
<div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>&#160;          buffer, lhs, rhs, triple_dim);</div>
<div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>&#160;    }</div>
<div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160;  }</div>
<div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160; </div>
<div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160;  <span class="keyword">template</span> &lt;TensorSycl::internal::contraction_type ct, <span class="keywordtype">bool</span> skinny, <span class="keyword">typename</span> input_mapper_properties,</div>
<div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>&#160;            <span class="keyword">typename</span> Properties, <span class="keyword">typename</span> LhsMapper, <span class="keyword">typename</span> RhsMapper&gt;</div>
<div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>&#160;  <span class="keywordtype">void</span> launchTT(EvaluatorPointerType buffer, <span class="keyword">const</span> LhsMapper &amp;lhs, <span class="keyword">const</span> RhsMapper &amp;rhs,</div>
<div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>&#160;                <span class="keyword">const</span> TripleDim &amp;triple_dim)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>&#160;    <span class="keyword">const</span> StorageIndex roundUpM = Eigen::TensorSycl::internal::roundUp(triple_dim.M, Properties::TileSizeDimM);</div>
<div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160;    <span class="keyword">const</span> StorageIndex roundUpN = Eigen::TensorSycl::internal::roundUp(triple_dim.N, Properties::TileSizeDimN);</div>
<div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160;    <span class="keyword">const</span> StorageIndex groupSizeM = roundUpM / Properties::TileSizeDimM;</div>
<div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160;    <span class="keyword">const</span> StorageIndex groupSizeN = roundUpN / Properties::TileSizeDimN;</div>
<div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160; </div>
<div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>&#160;    <span class="keyword">const</span> StorageIndex roundUpK = Eigen::TensorSycl::internal::roundUp(triple_dim.K, Properties::TileSizeDimK);</div>
<div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>&#160;    StorageIndex totalTilesK = roundUpK / Properties::TileSizeDimK;</div>
<div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>&#160;    StorageIndex groupSizeK =</div>
<div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>&#160;        skinny</div>
<div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>&#160;            ? std::max(std::min(totalTilesK,</div>
<div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>&#160;                                (StorageIndex)(device().getPowerOfTwo(device().getNumSyclMultiProcessors(), <span class="keyword">true</span>) * 4) /</div>
<div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160;                                    (groupSizeM * groupSizeN)),</div>
<div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160;                       StorageIndex(1))</div>
<div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>&#160;            : StorageIndex(1);</div>
<div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160; </div>
<div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>&#160;    <span class="keyword">const</span> StorageIndex numTilesPerGroup = Eigen::TensorSycl::internal::roundUp(totalTilesK, groupSizeK) / groupSizeK;</div>
<div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160; </div>
<div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160;    <span class="keyword">const</span> StorageIndex totalGroupSize = groupSizeM * groupSizeN * groupSizeK;</div>
<div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160; </div>
<div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>&#160;    <span class="keyword">const</span> StorageIndex localRange = Properties::LocalThreadSizeM * Properties::LocalThreadSizeN;</div>
<div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>&#160;    <span class="keyword">const</span> StorageIndex globalRange = totalGroupSize * localRange;</div>
<div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>&#160; </div>
<div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>&#160;    <span class="keyword">const</span> StorageIndex scratchSize = (ct == TensorSycl::internal::contraction_type::local)</div>
<div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>&#160;                                         ? ((Properties::DoubleBuffer + 1) *</div>
<div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>&#160;                                            (Properties::TileSizeDimM + Properties::BC) * (Properties::TileSizeDimK)) +</div>
<div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>&#160;                                               ((Properties::DoubleBuffer + 1) * (Properties::TileSizeDimK) *</div>
<div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>&#160;                                                (Properties::TileSizeDimN + Properties::BC))</div>
<div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>&#160;                                         : StorageIndex(1);</div>
<div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>&#160; </div>
<div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>&#160;    <span class="keyword">auto</span> thread_range = cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(globalRange), cl::sycl::range&lt;1&gt;(localRange));</div>
<div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>&#160;    <span class="keywordflow">if</span> (groupSizeK == 1) {</div>
<div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::TensorContractionKernel&lt;CoeffReturnType, LhsScalar, RhsScalar, EvaluatorPointerType,</div>
<div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>&#160;                                                            LhsMapper, RhsMapper, StorageIndex, Properties, TripleDim,</div>
<div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>&#160;                                                            PacketAccess, input_mapper_properties, <span class="keyword">true</span>, ct&gt;</div>
<div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160;          ContractKernelName;</div>
<div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(</div>
<div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160;          lhs, rhs, buffer, thread_range, scratchSize, groupSizeM, groupSizeN, numTilesPerGroup, triple_dim);</div>
<div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::TensorContractionKernel&lt;CoeffReturnType, LhsScalar, RhsScalar, EvaluatorPointerType,</div>
<div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160;                                                            LhsMapper, RhsMapper, StorageIndex, Properties, TripleDim,</div>
<div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>&#160;                                                            PacketAccess, input_mapper_properties, <span class="keyword">false</span>, ct&gt;</div>
<div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>&#160;          ContractKernelName;</div>
<div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>&#160;      CoeffReturnType *temp_pointer = <span class="keyword">static_cast&lt;</span>CoeffReturnType *<span class="keyword">&gt;</span>(</div>
<div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>&#160;          device().allocate_temp(triple_dim.M * triple_dim.N * groupSizeK * <span class="keyword">sizeof</span>(CoeffReturnType)));</div>
<div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>&#160;      EvaluatorPointerType tmp_global_accessor = device().get(temp_pointer);</div>
<div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160; </div>
<div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(</div>
<div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>&#160;          lhs, rhs, tmp_global_accessor, thread_range, scratchSize, groupSizeM, groupSizeN, numTilesPerGroup,</div>
<div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>&#160;          triple_dim);</div>
<div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>&#160; </div>
<div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160;      <span class="keyword">typedef</span> Eigen::internal::SumReducer&lt;CoeffReturnType&gt; Op;</div>
<div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>&#160;      <span class="keyword">auto</span> op = Op();</div>
<div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::SecondStepPartialReduction&lt;CoeffReturnType, StorageIndex, EvaluatorPointerType,</div>
<div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>&#160;                                                               EvaluatorPointerType, Op&gt;</div>
<div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>&#160;          ReductionKernel;</div>
<div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>&#160; </div>
<div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>&#160;      device().template unary_kernel_launcher&lt;CoeffReturnType, ReductionKernel&gt;(</div>
<div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>&#160;          tmp_global_accessor, buffer,</div>
<div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>&#160;          cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(StorageIndex(</div>
<div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>&#160;                                    Eigen::TensorSycl::internal::roundUp(triple_dim.M * triple_dim.N, localRange))),</div>
<div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>&#160;                                cl::sycl::range&lt;1&gt;(localRange)),</div>
<div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>&#160;          StorageIndex(1), op, StorageIndex(triple_dim.M * triple_dim.N), groupSizeK);</div>
<div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160; </div>
<div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>&#160;      device().deallocate_temp(temp_pointer);</div>
<div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>&#160;    }</div>
<div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>&#160;  }</div>
<div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>&#160; </div>
<div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_GEMV</span></div>
<div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>&#160;  <span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> is_lhs_vec, <span class="keyword">typename</span> VectorMapper, <span class="keyword">typename</span> TensorMapper, <span class="keyword">typename</span> StorageIndex&gt;</div>
<div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>&#160;  <span class="keywordtype">void</span> EIGEN_ALWAYS_INLINE LaunchVT(EvaluatorPointerType buffer, <span class="keyword">const</span> VectorMapper &amp;vec, <span class="keyword">const</span> TensorMapper &amp;mat,</div>
<div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>&#160;                                    StorageIndex NC, StorageIndex C)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>&#160;    <span class="keyword">const</span> StorageIndex nonContractDim = NC;</div>
<div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>&#160;    EIGEN_CONSTEXPR StorageIndex NCFactor = 1;</div>
<div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>&#160;    EIGEN_CONSTEXPR StorageIndex CFactor = 1;</div>
<div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160;    EIGEN_CONSTEXPR StorageIndex NCWindow = 16;</div>
<div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>&#160;    <span class="keyword">typedef</span> Eigen::TensorSycl::internal::TVPanelSize&lt;CoeffReturnType, StorageIndex, NCWindow, CFactor, NCFactor&gt;</div>
<div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160;        Properties;</div>
<div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160;    <span class="keyword">const</span> StorageIndex roundUpC = Eigen::TensorSycl::internal::roundUp(C, Properties::TileSizeDimC);</div>
<div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160;    <span class="keyword">const</span> StorageIndex cNumGroups = roundUpC / (Properties::LocalThreadSizeC * Properties::WorkLoadPerThreadC);</div>
<div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>&#160;    <span class="keyword">const</span> StorageIndex roundUpNC = Eigen::TensorSycl::internal::roundUp(nonContractDim, Properties::TileSizeDimNC);</div>
<div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>&#160;    <span class="keyword">const</span> StorageIndex nCNumGroups = roundUpNC / (Properties::LocalThreadSizeNC * Properties::WorkLoadPerThreadNC);</div>
<div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>&#160;    <span class="keyword">const</span> StorageIndex globalRange =</div>
<div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>&#160;        (roundUpNC / (Properties::WorkLoadPerThreadNC)) * (roundUpC / (Properties::WorkLoadPerThreadC));</div>
<div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>&#160;    <span class="keyword">const</span> StorageIndex localRange = Properties::LocalThreadSizeNC * Properties::LocalThreadSizeC;</div>
<div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>&#160;    <span class="keyword">const</span> StorageIndex scratchSize =</div>
<div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160;        (Properties::WorkLoadPerThreadNC + CFactor) * Properties::LocalThreadSizeC * Properties::LocalThreadSizeNC;</div>
<div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>&#160;    <span class="keyword">auto</span> thread_range = cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(globalRange), cl::sycl::range&lt;1&gt;(localRange));</div>
<div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>&#160;    <span class="keywordflow">if</span> (cNumGroups &gt; 1) {</div>
<div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160;      <span class="keyword">typedef</span> Eigen::TensorSycl::internal::GeneralVectorTensor&lt;CoeffReturnType, EvaluatorPointerType, VectorMapper,</div>
<div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160;                                                               TensorMapper, StorageIndex, Properties, CFactor, <span class="keyword">false</span>,</div>
<div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>&#160;                                                               is_lhs_vec, <span class="keyword">false</span>&gt;</div>
<div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160;          ContractKernelName;</div>
<div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>&#160;      CoeffReturnType *temp_pointer =</div>
<div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160;          <span class="keyword">static_cast&lt;</span>CoeffReturnType *<span class="keyword">&gt;</span>(device().allocate_temp(nonContractDim * cNumGroups * <span class="keyword">sizeof</span>(CoeffReturnType)));</div>
<div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>&#160;      EvaluatorPointerType tmp_global_accessor = device().get(temp_pointer);</div>
<div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>&#160; </div>
<div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(</div>
<div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160;          vec, mat, tmp_global_accessor, thread_range, scratchSize, nCNumGroups, nonContractDim, C);</div>
<div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>&#160; </div>
<div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>&#160;      <span class="keyword">typedef</span> Eigen::internal::SumReducer&lt;CoeffReturnType&gt; Op;</div>
<div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::SecondStepPartialReduction&lt;CoeffReturnType, StorageIndex, EvaluatorPointerType,</div>
<div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>&#160;                                                               EvaluatorPointerType, Op&gt;</div>
<div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160;          ReductionKernel;</div>
<div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>&#160; </div>
<div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160;      device().template unary_kernel_launcher&lt;CoeffReturnType, ReductionKernel&gt;(</div>
<div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>&#160;          tmp_global_accessor, buffer,</div>
<div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160;          cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(Eigen::TensorSycl::internal::roundUp(nonContractDim, localRange)),</div>
<div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160;                                cl::sycl::range&lt;1&gt;(localRange)),</div>
<div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160;          StorageIndex(1), Op(), nonContractDim, cNumGroups);</div>
<div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>&#160; </div>
<div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160;      device().deallocate_temp(temp_pointer);</div>
<div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>&#160;      <span class="keyword">typedef</span> Eigen::TensorSycl::internal::GeneralVectorTensor&lt;CoeffReturnType, EvaluatorPointerType, VectorMapper,</div>
<div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160;                                                               TensorMapper, StorageIndex, Properties, CFactor, <span class="keyword">false</span>,</div>
<div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>&#160;                                                               is_lhs_vec, <span class="keyword">true</span>&gt;</div>
<div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>&#160;          ContractKernelName;</div>
<div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(</div>
<div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>&#160;          vec, mat, buffer, thread_range, scratchSize, nCNumGroups, nonContractDim, C);</div>
<div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>&#160;    }</div>
<div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>&#160;  }</div>
<div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>&#160; </div>
<div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>&#160;<span class="preprocessor">#ifndef EIGEN_SYCL_DISABLE_SCALAR</span></div>
<div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> LhsMapper, <span class="keyword">typename</span> RhsMapper&gt;</div>
<div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>&#160;  EIGEN_ALWAYS_INLINE <span class="keywordtype">void</span> launchSC(EvaluatorPointerType buffer, <span class="keyword">const</span> LhsMapper &amp;lhs, <span class="keyword">const</span> RhsMapper &amp;rhs,</div>
<div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>&#160;                                    StorageIndex K)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>&#160;    EIGEN_STATIC_ASSERT(!((EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1) &amp;</div>
<div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>&#160;                          (EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1 - 1)),</div>
<div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160;                        <span class="stringliteral">&quot;The Local thread size must be a power of 2 for the reduction &quot;</span></div>
<div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160;                        <span class="stringliteral">&quot;operation&quot;</span>);</div>
<div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160;    EIGEN_CONSTEXPR StorageIndex local_range = EIGEN_SYCL_LOCAL_THREAD_DIM0 * EIGEN_SYCL_LOCAL_THREAD_DIM1;</div>
<div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160; </div>
<div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160;    <span class="comment">// Here we force the code not to be more than 2-step reduction: Our empirical research shows that if each thread</span></div>
<div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160;    <span class="comment">// reduces at least 512 elementss individually, we get better performance.</span></div>
<div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>&#160;    <span class="keyword">const</span> StorageIndex num_work_group = ((K + (512 * local_range - 1)) / (512 * local_range) &gt; 1 ? local_range : 1);</div>
<div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>&#160;    <span class="keyword">const</span> StorageIndex global_range = num_work_group * local_range;</div>
<div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160; </div>
<div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160;    <span class="keyword">typedef</span> Eigen::TensorSycl::internal::GeneralScalarContraction&lt;</div>
<div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160;        CoeffReturnType, LhsScalar, RhsScalar, EvaluatorPointerType, LhsMapper, RhsMapper, StorageIndex, <span class="keyword">false</span>&gt;</div>
<div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160;        ContractKernelName;</div>
<div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;    <span class="keyword">auto</span> thread_range = cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(global_range), cl::sycl::range&lt;1&gt;(local_range));</div>
<div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160;    <span class="keywordflow">if</span> (num_work_group &gt; 1) {</div>
<div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>&#160;      CoeffReturnType *temp_pointer =</div>
<div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160;          <span class="keyword">static_cast&lt;</span>CoeffReturnType *<span class="keyword">&gt;</span>(device().allocate_temp(num_work_group * <span class="keyword">sizeof</span>(CoeffReturnType)));</div>
<div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>&#160;      EvaluatorPointerType tmp_global_accessor = device().get(temp_pointer);</div>
<div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(lhs, rhs, tmp_global_accessor,</div>
<div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160;                                                                                    thread_range, local_range, K);</div>
<div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>&#160;      <span class="keyword">typedef</span> Eigen::internal::SumReducer&lt;CoeffReturnType&gt; Op;</div>
<div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>&#160;      <span class="keyword">typedef</span> TensorSycl::internal::SecondStepFullReducer&lt;CoeffReturnType, Op, EvaluatorPointerType,</div>
<div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>&#160;                                                          EvaluatorPointerType, StorageIndex, local_range&gt;</div>
<div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>&#160;          GenericRKernel;</div>
<div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>&#160;      device().template unary_kernel_launcher&lt;CoeffReturnType, GenericRKernel&gt;(</div>
<div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160;          tmp_global_accessor, buffer,</div>
<div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>&#160;          cl::sycl::nd_range&lt;1&gt;(cl::sycl::range&lt;1&gt;(local_range), cl::sycl::range&lt;1&gt;(local_range)), local_range, Op());</div>
<div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160; </div>
<div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160;      device().deallocate_temp(temp_pointer);</div>
<div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160;      device().template binary_kernel_launcher&lt;CoeffReturnType, ContractKernelName&gt;(lhs, rhs, buffer, thread_range,</div>
<div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>&#160;                                                                                    local_range, K);</div>
<div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160;    }</div>
<div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160;  }</div>
<div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160; </div>
<div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160;  EIGEN_STRONG_INLINE <span class="keywordtype">void</span> cleanup() {</div>
<div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;    this-&gt;m_leftImpl.cleanup();</div>
<div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>&#160;    this-&gt;m_rightImpl.cleanup();</div>
<div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>&#160; </div>
<div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>&#160;    <span class="keywordflow">if</span> (this-&gt;m_result) {</div>
<div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>&#160;      this-&gt;m_device.deallocate_temp(this-&gt;m_result);</div>
<div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160;      this-&gt;m_result = NULL;</div>
<div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>&#160;    }</div>
<div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>&#160;  }</div>
<div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>&#160;  <span class="comment">// The placeholder accessors must bound to a command group handler for SYCL</span></div>
<div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160;  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE <span class="keywordtype">void</span> bind(cl::sycl::handler &amp;cgh)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>&#160;    this-&gt;m_leftImpl.bind(cgh);</div>
<div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>&#160;    this-&gt;m_rightImpl.bind(cgh);</div>
<div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>&#160;    this-&gt;m_result.bind(cgh);</div>
<div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>&#160;  }</div>
<div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>&#160;};</div>
<div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>&#160;}  <span class="comment">// namespace Eigen</span></div>
<div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>&#160;<span class="preprocessor">#endif  </span><span class="comment">// EIGEN_CXX11_TENSOR_TENSOR_CONTRACTION_SYCL_H</span></div>
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